This document outlines a study examining the effects of maternal obesity on monoamine systems in mice offspring. The study found that maternal high fat diet disrupted dopamine, serotonin, and norepinephrine levels in brain regions of postnatal day 10 mice pups, particularly in females. Dopamine levels were affected in the prefrontal cortex and hippocampus, serotonin in the prefrontal cortex, hippocampus and cerebellum, and norepinephrine in several brain regions, in a sex-specific manner. This suggests maternal high fat diet may influence early brain development and put offspring at risk for conditions like autism spectrum disorder. Future research is needed to further investigate these effects and connections to behavior and biomarkers.
Menopausal hormone therapy (MHT) also called postmenopausal hormone therapy and hormone replacement therapy. Here is presentation on Menopausal hormone therapy by Dr. Laxmi Shrikhande
Menopausal hormone therapy (MHT) also called postmenopausal hormone therapy and hormone replacement therapy. Here is presentation on Menopausal hormone therapy by Dr. Laxmi Shrikhande
It is the term used for people whose height is below the average compared to their peers’ height. This term is most commonly used for children, but also can be applied to adults. As children can be shorter than their friends or peers and still perfectly healthy. This case occur when the adult height is more than two standard deviations less than the known degree of shortness.
Causes and classification:
1- Structural growth delay:
Simply, in children the growth may be delayed than others, which are called late bloomers. They usually reach the puberty later than children of their age, and their growth will continue after others of the same age and the normal height rate.
2- Genetically:
It may called familial short stature or genetic short stature. In this case the person will have abnormal height rate lower than others at the same age throughout his life. . The bone age formation is with the chronological age. This is the most difference between the familial short stature and those of delayed growth.
3- Disease:
- Endocrine diseases: which will affect the production of hormones. Some of this hormones that affects the growth and the height are thyroxin (hypothyroidism), growth hormone (growth hormone deficiency), and Cushing’s disease.
- Chronic diseases: they effect on the overall health. Such as, kidney disease, heart problems, bronchial asthma, bowel inflammation, diabetes, rheumatoid arthritis, and sickle cell anaemia.
- Genetic conditions: Down syndrome, Williams syndrome, and turner syndrome.
- Skeletal and bone diseases: rickets, achondroplasia that change the structure by their effect on the growth of bones.
4
- Also some problems or diseases during pregnancy or malnutrition have effects on the height of the child. (Lacey et al, 1974)
4- Other normal and biological causes:
- According to Binder (2011), it is a case in which the person is 2 SD from the known normal ranges, and there is no evidence for endocrine problems or delayed growth. The short stature, in this case, occur due to some variations (genetic variations) which have large effects, such as SHOX gene. This gene is responsible for 1% to 4% of the cases of the short stature. This is known by Idiopathic short stature.
- Some causes of short stature cases may be because of the premature delivery of infants. Premature infants continue with this problem to the childhood, which is known by small for gestational age.
- Cartilage extracellular matrix as the collagen and another proteins that is responsible for the growth of cartilage.
- Control of growth plate function by the effect of cytokines, so the repeated inflammatory diseases cause slowing of the growth plate, because the catch up of the growth delayed after the effect of cytokines resolved.
Since the first formal description of LPD in 1949 as a possible cause of infertility and recurrent miscarriage by Jones. Innumerable investigations have been undertaken in an effort to verify its existence or to characterize its pathophysiology, diagnosis, and treatment. The consensus of the literature is that LPD does exist and that its cause is multifactorial like abnormal folliculogenesis, inadequate LH surge,inadequate secretion of progesterone by the corpus luteum, aberrant end-organ response by the endometrium.
Obstetric outcomes associated with second trimester unexplained abnormal mate...Apollo Hospitals
1) To compare the adverse obstetrical outcomes in the patient population with normal blood MoMs.
2) To determine the probability of occurrence of an adverse obstetric event in relation with abnormal maternal blood
analytes.
It is the term used for people whose height is below the average compared to their peers’ height. This term is most commonly used for children, but also can be applied to adults. As children can be shorter than their friends or peers and still perfectly healthy. This case occur when the adult height is more than two standard deviations less than the known degree of shortness.
Causes and classification:
1- Structural growth delay:
Simply, in children the growth may be delayed than others, which are called late bloomers. They usually reach the puberty later than children of their age, and their growth will continue after others of the same age and the normal height rate.
2- Genetically:
It may called familial short stature or genetic short stature. In this case the person will have abnormal height rate lower than others at the same age throughout his life. . The bone age formation is with the chronological age. This is the most difference between the familial short stature and those of delayed growth.
3- Disease:
- Endocrine diseases: which will affect the production of hormones. Some of this hormones that affects the growth and the height are thyroxin (hypothyroidism), growth hormone (growth hormone deficiency), and Cushing’s disease.
- Chronic diseases: they effect on the overall health. Such as, kidney disease, heart problems, bronchial asthma, bowel inflammation, diabetes, rheumatoid arthritis, and sickle cell anaemia.
- Genetic conditions: Down syndrome, Williams syndrome, and turner syndrome.
- Skeletal and bone diseases: rickets, achondroplasia that change the structure by their effect on the growth of bones.
4
- Also some problems or diseases during pregnancy or malnutrition have effects on the height of the child. (Lacey et al, 1974)
4- Other normal and biological causes:
- According to Binder (2011), it is a case in which the person is 2 SD from the known normal ranges, and there is no evidence for endocrine problems or delayed growth. The short stature, in this case, occur due to some variations (genetic variations) which have large effects, such as SHOX gene. This gene is responsible for 1% to 4% of the cases of the short stature. This is known by Idiopathic short stature.
- Some causes of short stature cases may be because of the premature delivery of infants. Premature infants continue with this problem to the childhood, which is known by small for gestational age.
- Cartilage extracellular matrix as the collagen and another proteins that is responsible for the growth of cartilage.
- Control of growth plate function by the effect of cytokines, so the repeated inflammatory diseases cause slowing of the growth plate, because the catch up of the growth delayed after the effect of cytokines resolved.
Since the first formal description of LPD in 1949 as a possible cause of infertility and recurrent miscarriage by Jones. Innumerable investigations have been undertaken in an effort to verify its existence or to characterize its pathophysiology, diagnosis, and treatment. The consensus of the literature is that LPD does exist and that its cause is multifactorial like abnormal folliculogenesis, inadequate LH surge,inadequate secretion of progesterone by the corpus luteum, aberrant end-organ response by the endometrium.
Obstetric outcomes associated with second trimester unexplained abnormal mate...Apollo Hospitals
1) To compare the adverse obstetrical outcomes in the patient population with normal blood MoMs.
2) To determine the probability of occurrence of an adverse obstetric event in relation with abnormal maternal blood
analytes.
Boiler control panel manufacturers Ahmedabad,Power Distribution Panel,Electrical Control Panel Gujarat,MCC panel manufacturer,APFC panel suppliers
For more details visit us http://www.alfapowercontrols.com at:
LED lights are more than just the future of lighting. From the past years, its innovation has led to thousands of improvement to various branches of the technological industry and devices such as LCD TVs, traffic signs, phones, mobile devices, led signs and etc. But other than that, LEDs do have and offer different benefits.
To learn more and watch the webinar, visit:
https://insidescientific.com/webinar/brain-circuits-driving-appetite-obesity-2020
In many western countries, nearly a quarter of us meet the criteria for clinical obesity and more than half of us are overweight. This is a medical concern because obesity is a serious risk factor for many major chronic illnesses, such as heart disease, type 2 diabetes and cancer, and as a result, obesity is associated with reduced lifespan by almost a decade. The rapid escalation in the prevalence of obesity and the paucity of obesity medications underscores the necessity of an understanding of the basic neurobiology underlying body weight.
During this webinar, Professor Heisler will discuss brain circuits that are the main known controllers of body weight, such as those activated by the adipocyte hormone leptin. She will review how our genes impact our waistline and will discuss crucial genes such as those in the melanocortin system. Professor Heisler will discuss how obesity medications capitalize on this basic neurobiology to promote satiety, reduce hunger and decrease body weight.
Key discussion topics include:
– Gut to brain communication
– Key brain chemicals mediating satiety
– Key brain chemicals controlling hunger
Managing DM and thyroid disease in shift workersNemencio Jr
This slide deck discusses the effects of shift work on physiology and behavior of thyroid axis and beta cell function and risk of diabetes, including glucose control among those with diabetes. Management strategies are also discussed
Recurrent pregnancy loss (RPL), also referred to as recurrent miscarriage or habitual abortion, is historically defined as 3 consecutive pregnancy losses prior to 20 weeks from the last menstrual period.
This Presentation is made by Dr.Laxmi Shrikhande
(First slide is recording of webinar). IUPHAR Web Resources, Simplifying Complexity for Medicine and Education. WDS Webinar#11 held on 28th February 2017.
IUPHAR (International Union of Basic and Clinical Pharmacology) has developed and is developing a series of web-based services for the Pharmacological Sciences, for education, and for drug discovery. These services enable the simplification and dissemination of highly complex datasets, via expert committees linked to ontologically-correct databases (e.g., the drug and receptor sites expressed by the human genome). This has also allowed IUPHAR—in connection with the main national pharmacological societies, particularly the British Pharmacological Society—to raise funds for curators and meetings. This simple model is open-ended and is being expanded to, for example, immunological targets and experimental protocols, and to educational projects.
Speakers: Michael Spedding, Adam Pawson, Steve Alexander, Joanna Sharman, Simon Harding, Jamie Davies, John Szarek and Lynn LeCount
20180202 3 j. lombard genomind milan relazione part 2 to pub.pptxRoberto Scarafia
https://www.linkedin.com/pulse/simposio-toma-implementazione-della-farmacogenetica-nel-scarafia/
https://www.linkedin.com/pulse/malattie-psichiatriche-e-neurologiche-arriva-toma-il-test-scarafia/
2 febbraio 2018, Sala Congressi Laboratorio TOMA
Relatori: Dr. J. Lombard, Dr.ssa F.R. Grati, Dr.ssa S. De Toffol
BREVE PREMESSA
La farmacogenetica studia l’influenza dei fattori genetici sull’attività di un farmaco, la sua assimilazione e il suo metabolismo allo scopo di massimizzarne l’efficacia terapeutica e minimizzare gli effetti avversi. I fattori genetici possono giustificare fino al 95% della variabilità interpersonale nella risposta e nelle reazioni avverse a determinati trattamenti farmacologici. Finora la diagnosi ed il trattamento farmacologico in psichiatria si sono basati principalmente sul un protocollo ‘trial and error’ tramite colloquio, osservazione clinica e analisi di laboratorio costituivano esclusivamente un complemento per valutare possibili effetti collaterali o i livelli plasmatici di alcuni farmaci. L’introduzione di test di farmacogenetica consente di fornire al clinico informazioni costitutive dell’individuo relativamente al metabolismo di molti farmaci e la potenziale risposta in determinati contesti clinici al fine di ridurre i tempi ottenimento del trattamento efficace personalizzato e arricchire con le più recenti informazioni genetiche la gestione terapeutica dei pazienti.
OBIETTIVI FORMATIVI
Introdurre i principi scientifici alla base del test genetico che si presenterà durante il corso, il significato, la funzione e la rilevanza clinica per la salute mentale di ciascun gene indagato dal test;
L’utilità clinica del test Genecept: presentare come vengono riportati i risultati del test e come meglio interpretarli;
Presentare alcuni casi clinici reali per discutere circa l’utilità di un trattamento farmacologico guidato dai risultati del test genetico rispetto all’approccio tradizionale ‘trial and error’
CLARITY BPA: a Novel Approach to study EDCsDES Daughter
by the Collaborative on Health and the Environment
On this call Retha Newbold, MS, Researcher Emeritus, National Toxicology Program, National Institute of Environmental Health Sciences, discussed the program called “The Consortium Linking Academic and Regulatory Insights on the Toxicity of Bisphenol A (CLARITY-BPA)” which is an interagency agreement, conducted under the auspices of the National Toxicology Program (NTP), between The National Institute of Environmental Health Sciences (NIEHS) supported grantees, the staff of the Division of the National Toxicology Program (DNTP) at NIH/NIEHS, and the Food and Drug Administration at the National Center for Toxicological Research (FDA/NCTR). The goals of the consortium are to enhance the utility of a perinatal 2-year GLP chronic toxicity study on BPA for regulatory decision-making by incorporating a wide range of doses and some additional disease-related endpoints that are not usually covered.
To this end, 12 NIEHS grantees are studying hypothesis-driven mechanisms by investigating specific endpoints that maybe altered by BPA including behavioral/neuroendocrine, immune function, cardiac, reproductive tract, cancer, thyroid, and other organ systems. This consortium is unique in that it combines the knowledge and skills of the NTP staff with experts from the academic field who are covering more mechanistic studies. Although this program focuses on BPA, it may provide an example of how to better study effects of other endocrine disrupting chemicals especially since numerous organ systems may be involved.
Sources: http://www.healthandenvironment.org/partnership_calls/14639
Biomedical big data and research clinical application for obesityHyung Jin Choi
1. What is Biomedical Big Data?
2. Biomedical Big Data
1) Genetic Data
2) Electrical Health Records
3) National Healthcare Data
4) Medical Images
5) Sensor/Mobile Data
6) Data Integration
3. Biomedical Big Data + Artificial Intelligence
4. Research/Clinical Application for Obesity
"How Scientific Wellness will Drive The Future of Health" - Nathan Price (Pro...Hyper Wellbeing
"How Scientific Wellness will Drive The Future of Health" - Nathan Price (Professor, Institute of Systems Biology)
Delivered at the inaugural Hyper Wellbeing Summit, 14th November 2016, Mountain View, California.
For more information including details of subsequent events, please visit http://hyperwellbeing.com
The summit was created to foster a community around an emerging industry - Wellness as a Service (WaaS). Consumer technologies, in particular wearables and mobile, are powering a consumer revolution. A revolution to turn health and wellness into platform delivered services. A revolution enabling consumer data-driven disease risk reduction. A revolution extending health care past sick care towards consumer-led lifelong health, wellness and lifestyle optimization.
WaaS newsletter sign-up http://eepurl.com/b71fdr
@hyperwellbeing
What is gut microbiota? What is the influence of diet on the proper functioning of our gut microbiota? How does the gut-brain axis (GBA) influence the emotional and cognitive centers of the brain? Tune into this webinar to find out more about this timely topic.
Learning Objectives:
List the neurological and physiological connections that enable the bidirectional communication between the gut and the brain
Identify lifestyle, dietary, and microbial influences on the flow and function of signaling molecules along the gut-microbiota-brain axis
Implement dietary regimens that target the gut and gastrointestinal microbiota to improve or maintain optimal physical and mental health
RDNs earn 1.0 CEU
Hormones, Cognition, and Mood Changes in Older AdultsLouis Cady, MD
HORMONES, COGNITION AND MOOD CHANGES IN OLDER ADULTS. This is Dr. Cady's lecture from the Age Management Medical Group meeting in las Vegas, NV, PRESENTED 12 2 2012.
Works Cited Milne, Anne C., Alison Avenell, and Jan Potter. Meta-.docxkeilenettie
Works Cited
Milne, Anne C., Alison Avenell, and Jan Potter. "Meta-Analysis: Protein and Energy Supplementation in Older People."
Annals of Internal Medicine
144.1 (2006): 37-48.
ProQuest.
Web. 1 Oct. 2014.
Meta-Analysis: Protein and Energy Supplementation in Older People Anne C. Milne, MSc; Alison Avenell, MD; and Jan Potter, MBChB Background: Protein and energy undernutrition is common in older people, and further deterioration may occur during illness. Purpose: To assess whether oral protein and energy supplementa tion improves clinical and
nutritional outcomes for older people in the hospital, in an institution, or in the community. Data Sources: Cochrane Central Register of Controlled Trials (CEN TRAL), MEDLINE, EMBASE,
HealthStar, CINAHL, BIOSIS, and CAB abstracts. The authors included English- and non-English-language studies and hand-searched journals, contacted manufacturers, and sought information from trialists. The date of the most recent search of CENTRAL and MEDLINE is June 2005. Study Selection: Randomized and quasi-randomized controlled tri als of oral protein and energy
supplementation compared with placebo or control treatment in older people. Data Extraction: Two reviewers independently assessed trials for inclusion, extracted data, and assessed trial quality. Differences were resolved by consensus. Data Synthesis: Fifty-five trials were included (n = 9187 randomly tions (Peto odds ratio, 0.72 [95% Cl, 0.53 to 0.97]) and reduced mortality (Peto odds ratio, 0.66 [CI, 0.49 to 0.90]) for those un dernourished at baseline. Few studies reported evidence that suggested any change in mortality, morbidity, or function for those given supplements at home. Ten trials reported gastrointestinal disturbances, such as nausea, vomiting, and diarrhea, with oral supplements. Limitations: The quality of most studies, as reported, was poor, particularly for concealment of allocation and blinding of outcome assessors. Many studies were too small or the follow-up time was too short to detect a statistically significant change in clinical out come. The clinical results are dominated by 1 very large recent trial in patients with stroke. Although this was a high-quality trial, few participants were undernourished at baseline. Conclusions: Oral nutritional supplements can improve nutritional status and seem to reduce mortality and complications for under nourished elderly patients in the hospital. Current evidence does not support routine supplementation for older people at home or for well-nourished older patients in any setting. assigned participants). For patients in short-term care hospitals who were given oral supplements, evidence suggested fewer complica-Ann Intern Med. 2006:144:37-48. For author affiliations, see end of text.
www.annals.OIJ
ndernutrition among older people is a continuing source of concern (1, 2). Older people have longer periods of illness and longer hospital stays (3), and data show tha.
1. Dylan M. Djani
Mentor: Nikolay M. Filipov
Department of Physiology and Pharmacology
College of Veterinary Medicine
University of Georgia
2. Presentation Outline
• Obesity and Autism Spectrum Disorder (ASD)
– Prevalence, key features
• ASD Etiology
– Maternal environment
• Early Brain Monoamines
What are
monoamines?
(Bear et. al., 2015)
3. Obesity Trends in the U.S.
National Health and Nutrition Examination Survey (NHANES)
• Obesity Prevalence in U.S. Adults ≥ 25 years [2007 – 2012]
– Men: 35.04% Data published June 22, 2015 (Yang and Colditz, 2015)
– Women: 36.84%
Prevalence consistently high [2003 – 2010]
Data published February 26, 2014 (Ogden et. al., 2014)
Obesity – chronic inflammatory condition:
risk mortality, physical, emotional, and mental conditions
OVER 1 in 3 AMERICANS
Regardless of sex or race
(Monteiro and Azevedo, 2010; Nijhuis et. al., 2009)
4. Maternal Obesity Trends in the U.S.
Schlaff et. al., 2014
*Gestational weight gain; 1Archive for Research on Child Health
Overweight and obese women are more likely to gain excess weight during pregnancy.
>50% women gained excess weight during gestation. (2009 Institute of Medicine)
5. Maternal Obesity
Adversely Impacts
Offspring
Rivera et. al., 2015
BMI:
Body mass index
GWG:
Gestational weight gain
HFD:
High-fat diet
Rivera et. al., 2015
Human research studies
Animal model research studies
6. Autism-Spectrum Disorder: Overview
DSM-V: Neurodevelopmental Disorder
Early onset and lifelong impact (APA, 2013)
Core symptoms: deficits in communication, social interaction, behavior
http://www.autismspeaks.org/
Last updated January 6, 2015
Prevalence Facts:
*1 in 68 children in the U.S.
*Male bias (M/F Sex Ratio 4:1)
*Positive correlation with obesity
123% increase in ASD
prevalence since 2002.
Analysis of 2010 data; published in 2014; studies ongoing (ADDM)
CDC Autism and Developmental Disabilities Monitoring Network
9. Maternal Obesity in the Perinatal Period
Maternal obesity
(Rivera et. al., 2015; Sullivan et. al., 2015; Mehta et. al., 2014; Bolton and Bilbo, 2014)
Immunologic dysregulation
Altered placental function
Maternal circulation
Pro-inflammatory cytokines
Glucose and triglycerides
Hormones (i.e. leptin)
Serotonin (5-HT)
Altered fetal exposure
during perinatal period
Altered brain connectivity and neurotransmitter systems
Epigenetic, metabolic, neurobehavioral programming
10. Monoaminergic Involvement in ASD: Serotonin
Jaiswal et. al., 2015
Neuroimmunologic dysregulation in ASD involves serotonin.
11. Monoaminergic Involvement in ASD
Dopaminergic System Noradrenergic System
ASD Psychiatric comorbidities
Cross-talk between DA and NE
Brainstem (VTA, LC)
Dorsal hippocampus
(Hara et. al., 2015; Kriete and Noelle, 2015) (Jellinger, 2011; Guiard et. al., 2008)
Prefrontal Cortex
Valproic-acid mouse model: PND21
Computerized developmental modeling
Rivera et. al., 2015
12. Experimental Objectives
Evaluate the effects of maternal obesity and sex on
monoamine systems in the early post-natal life of mice.
Hypothesis
Significant neurochemical differences will be observed
in selected brain regions of post-natal day 10 mice due
to maternal high fat diet and sex.
13. Experimental Design and Timeline
Brain Collection: PND10
N = 7; 1m/1f per group
Brain Region Collection:
500 μm coronal sectioning; dry ice
Regional micropunches obtained
Animals:
C57BL/6 female mice, 6-7 weeks
Assigned Diet*:
High fat: 60% kcal from fat HFD
Low fat: 10% kcal from fat LFD
PND = post-natal day; *Diets balanced for simple sugars and micronutrients.
*Assigned diets maintained throughout weaning (PND21).
WEEK 0
Maternal
diets
assigned
WEEK 6
Mating with
control males.
PND 0
Pups born.
PND 10
Pups selected for
brain collection.
Brain region collection
Neurochemical analysis
14. Materials and Methods
Monoamine and Metabolite Analytes:
Dopaminergic System: DA, DOPAC, HVA, 3-MT
Serotonergic System: 5-HT, 5-HIAA
Noradrenergic System: NE, MHPG
Brain regions collected:
Prefrontal cortex (PFC)
Striatum (STR)
Dorsal Hippocampus (dHIPP)
Ventral Hippocampus (vHIPP)
Cerebellum (CER)
Neurochemical Analysis: HPLC-ECD + Bradford Assay
Data normalized per mg protein prior to statistical analysis
Data Processing and Presentation:
Performed with Microsoft Excel, SigmaPlot, GraphPad Prism 5 software
15. Comparative Mammalian Neurodevelopment
“Translating Time” Across Mammals – Why PND10?
Assumptions:
Mouse gestation length: 18.5 days
Human gestation length: 270 days (~38.5 weeks)
(Workman et. al., 2013)
Including synaptogenesis!
Mouse PND10 equivalent to late third trimester in
terms of neurodevelopment.
16. Critical Windows – Why Post-Natal Day 10?
Significantly increased rates of AXONAL GROWTH and SYNAPTOGENESIS
during the late third trimester of human gestation.
Vertes and Bullmore, 2015
Critical window for cortical wiring of neuronal circuitries and neurotransmitter systems.
Added benefit: offspring nutritional source is maternal lactation.
17. RESULTS
Dopaminergic
dysregulation.
Possible behavioral
consequences
(i.e. hyperactivity).
*Statistically significant main effect of diet. aStatistically significant effect of diet within females.
#Statistical trend for main effect of diet. ^Statistical trend for effect of diet within females.
Prefrontal Cortex: Dopamine
LFD
H
FD
LFD
H
FD
0.0
0.1
0.2
0.3
0.4
Males Females
DA(ng/mgprotein)
*
a
Dorsal Hippocampus: Dopamine
LFD
H
FD
LFD
H
FD
0.000
0.125
0.250
0.375
0.500
Males FemalesDA(ng/mgprotein)
*
^ LFD
HFD
Ventral Hippocampus: Dopamine
LFD
H
FD
LFD
H
FD
0.00
0.75
1.50
2.25
3.00
Males Females
DA(ng/mgprotein)
*
^
Ventral Hippocampus: DOPAC
LFD
H
FD
LFD
H
FD
0.0
0.5
1.0
1.5
2.0
Males Females
DOPAC(ng/mgprotein)
#
18. RESULTS
Serotonergic
dysregulation
(female-restricted)
Possible
communication or
social interaction
deficits.
*Statistically significant main effect of sex. aStatistically significant effect of diet within females.
#Statistical trend for main effect of diet. ^Statistical trend for effect of diet within females.
Prefrontal Cortex: 5-HT
LFD
H
FD
LFD
H
FD
0.000
0.375
0.750
1.125
1.500
Males Females
5-HT(ng/mgprotein)
^
*
Prefrontal Cortex: 5-HIAA
LFD
H
FD
LFD
H
FD
0.0
0.5
1.0
1.5
2.0
Males Females
5-HIAA(ng/mgprotein)
^
Ventral Hippocampus: 5-HT
LFD
H
FD
LFD
H
FD
0
2
4
6
8
Males Females
5-HT(ng/mgprotein)
a
Cerebellum: 5-HT
LFD
H
FD
LFD
H
FD0
2
4
6
8
Males Females
5-HT(ng/mgprotein)
*
^ LFD
HFD
19. RESULTS
Sex-specific
noradrenergic
differences.
*Statistically significant main effect of sex.
#Statistical trend for main effect of sex.
Prefrontal Cortex: NE
LFD
H
FD
LFD
H
FD
0.0
0.5
1.0
1.5
2.0
Males Females
NE(ng/mgprotein)
#
Cerebellum: NE
LFD
H
FD
LFD
H
FD
0
2
4
6
8
Males Females
NE(ng/mgprotein)
*
Dorsal Hippocampus: NE
LFD
H
FD
LFD
H
FD
0.0
0.5
1.0
1.5
2.0
2.5
Males Females
NE(ng/mgprotein)
*
Ventral Hippocampus: NE
LFD
H
FD
LFD
H
FD
0
1
2
3
Males Females
NE(ng/mgprotein)
*
Female:
NE PFC, vHIPP, CER
NE dHIPP
Positive correlation between
female-restricted maternal HFD
effects on 5-HT and female-
specific NE differences.
20. Conclusion
Maternal HFD disrupts monoamine systems at PND10 in mice in a
sex-specific manner, consistent with altered brain neurochemistry
and connectivity.
Data suggests maternal HFD may put offspring on a trajectory
towards ASD.
Future Research:
Monoamine turnover rate analysis via NT/metabolite ratios.
Biomarker analysis of dopaminergic dysfunction in PFC, dHIPP, vHIPP
Western Blot + qPCR (qPCR samples obtained for HIPP)
Integration with neurochemical data at other time points.
Integration with behavioral data and immunologic assessment.
21. General and Funding Acknowledgements
Department of Physiology and Pharmacology
Saritha Krishna John J. Wagner Sadie E. Nennig Nikolay M. Filipov
Department of Infectious Diseases
Donald A. Harn
Department of Foods and Nutrition
Claire B. de La Serre
Miscellaneous
Annika Carter
The project described was supported by Grant
Number 05 T35 OD010433-09 from the National
Center for Research Resources (NCRR), a
component of the National Institutes of Health
(NIH) and its contents are solely the responsibility
of the authors and do not necessarily represent
the official view of NCRR or NIH.
Funding was also provided by through a grant
from the University of Georgia’s Obesity Initiative
(http://obesity.ovpr.uga.edu).
Editor's Notes
Neurochemical deficits in offspring of dams (mothers) fed high-fat diets.
In particular, we will focus on the effects on brain monoamines.
“Biogenic amines” – AA neurotransmitters
Synaptic transmission – form brain circuits.
Diffuse projections throughout forebrain/striatum
Focus on DA, 5-HT, NE
M. F. Bear, B. W. Connors, M. A. Paradiso, Neuroscience : exploring the brain. (Lippincott Williams & Wilkins, ed. 4, 2015).
Chronic inflammatory condition: multifactorial, mechanisms include adipocyte-sourced pro-inflammatory cytokines, involvement of other pro-inflammatory mediators, and cell rupture and ensuing inflammation.
Yang L, Colditz GA. Prevalence of overweight and obesity in the united states, 2007-2012. JAMA Internal Medicine. 2015.
Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the united states, 2011-2012. JAMA. 2014;311(8):806-14.
R. Monteiro, I. Azevedo, Chronic Inflammation in Obesity and the Metabolic Syndrome. Mediators of Inflammation 2010, 289645 (2010).
J. Nijhuis et al., Neutrophil activation in morbid obesity, chronic activation of acute inflammation. Obesity (Silver Spring) 17, 2014-2018 (2009).
Guidelines (2013) for managing overweight and obesity in adults. Preface to the Expert Panel Report (comprehensive version which includes systematic evidence review, evidence statements, and recommendations). Obesity (Silver Spring) 22 Suppl 2, S40 (2014).
Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults--The Evidence Report. National Institutes of Health. Obes Res 6 Suppl 2, 51S-209S (1998).
This epi study assessed GWG via two methods – the ARCH method was more robust.
Obese trend slightly less strong than overweight trend – suggests threshold of sort.
2014 cohort study re: pre-pregnancy BMI, body size, GWG, and physical activity.
Data collected 2008-2012 via women participating in ARCH1 study in Michigan.
ARCH calculations more robust than birth certificate calculations.
Schlaff RA, Holzman C, Maier KS, Pfeiffer KA, Pivarnik JM. Associations among gestational weight gain, physical activity, and pre-pregnancy body size with varying estimates of pre-pregnancy weight. Midwifery. 2014 11//;30(11):1124-31.
ARCH = Archive for Research on Child Health – study to collect and store record information re: pregnancy, perinatal urine/blood/placenta samples, etc.
Birth certificate information depends on weight from records and hospital variation in such procedures makes it less robust (self-reporting vs. actually weighing etc.)
ARCH calculated BMI from information collected systematically (kg weight / m^2 height upon patient reporting) as well as using weight recorded on birth certificates
2015 publication describing neuropsychiatric risk and maternal obesity factors.
Increased risk of ASD, anxiety/depression, and schizophrenia were associated with increased gestational weight gain.
H. M. Rivera, K. J. Christiansen, E. L. Sullivan, The role of maternal obesity in the risk of neuropsychiatric disorders. Frontiers in Neuroscience 9, 194 (2015).
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.
Prevalence of autism spectrum disorder among children aged 8 years - autism and developmental disabilities monitoring network, 11 sites, United States, 2010. MMWR Surveill Summ. 2014 Mar 28;63(2):1-21.
https://www.autismspeaks.org/science/science-news/can-rise-autism-be-explained-broadened-diagnosis
Accessed June 25, 2015.
Demonstrates neuroimmunologic implications.
Recall maternal obesity increasing risk for ASD and some of the psychiatric comorbidities listed above.
Chen M-H, Wei H-T, Chen L-C, et al. Autistic spectrum disorder, attention deficit hyperactivity disorder, and psychiatric comorbidities: A nationwide study. Research in Autism Spectrum Disorders. 2015 2//;10(0):1-6.
Zerbo O, Leong A, Barcellos L, Bernal P, Fireman B, Croen LA. Immune mediated conditions in autism spectrum disorders. Brain, Behavior, and Immunity. 2015 5//;46(0):232-6.
OUR EXPERIMENTAL DESIGN INTENDS TO FOCUS IN ON PERINATAL MONOAMINERGIC EFFECTS OF MATERNAL OBESITY using mice models in a controlled experiment.
Tying together information from animal models and epidemiological studies, two key characteristics of autism include altered brain connectivity, ultimately from dysregulation at the level of the synapse, as well as alterations in the innate immune system particularly of a pro-inflammatory nature.
Teasing apart etiological factors for ASD involves identifying genetic and environmental contributions, as well as how their interactions contribute to ASD etiology.
Here we see the narrow-sense heritability for ASD is estimated around 52%, thus environmental factors and gene-environment interactions play roughly an equally important role in ASD. Furthermore, the largest contribution to this 52% is from common genetic variation in the population, with only ~2.6% coming from rare mutations in genes involved with synaptic regulation, among other fundamental intracellular processes (cytoskeletal function, cell adhesion/growth)
The maternal environment, in particular the perinatal intrauterine environment, has emerged as a key environmental factor impacting offspring development and behavior. Furthermore, the role of epigenetics in synaptic and immunologic regulation has also emerged as a key factor through mediating gene-environment interactions. What this means is that an individual’s epigenetic make-up is influenced by the maternal environment and affects neurodevelopment. What about maternal obesity in particular?
Genes involved include those that directly and epigenetically regulate several aspects of synaptic homeostasis and immune pathways, as well as other basic intracellular processes. Some studies suggest involvement of genes involved in toxicant excretion from the CNS, though these overlap with immune pathways. (Rusu et. al., 2015; Medzhitov, 2008).
C. Rusu, C. Preda, A. Sireteanu, C. Vulpoi, RISK FACTORS IN AUTISM SPECTRUM DISORDERS: THE ROLE OF GENETIC, EPIGENETIC, IMMUNE AND ENVIRONMENTAL INTERACTIONS. Environmental Engineering & Management Journal (EEMJ) 14, 901-917 (2015).
R. Medzhitov, Origin and physiological roles of inflammation. Nature 454, 428-435 (2008).
Environmental toxicants
Disruption of perinatal uterine environment leads to programming of offspring metabolically and neurobehaviorally.
Banerjee S, Riordan M, Bhat MA. Genetic aspects of autism spectrum disorders: insights from animal models. Frontiers in Cellular Neuroscience. 2014 02/24. 01/02/received.
Kana RK, Uddin LQ, Kenet T, Chugani D, Müller R-A. Brain connectivity in autism. Frontiers in Human Neuroscience. 2014 06/02. 03/05/received. 05/08/accepted;8:349.
Hahamy A, Behrmann M, Malach R. The idiosyncratic brain: distortion of spontaneous connectivity patterns in autism spectrum disorder. Nat Neurosci. 2015 02//print;18(2):302-9.
Jaiswal P, Mohanakumar KP, Rajamma U. Serotonin mediated immunoregulation and neural functions: Complicity in the aetiology of autism spectrum disorders. Neuroscience & Biobehavioral Reviews. 2015 8//;55(0):413-31.
Gaugler T, Klei L, Sanders SJ, et al. Most genetic risk for autism resides with common variation. Nat Genet. 2014 08//print;46(8):881-5.
Tamashiro KL, Moran TH. Perinatal environment and its influences on metabolic programming of offspring. Physiol Behav. 2010 Jul 14;100(5):560-6.
Loke YJ, Hannan AJ, Craig JM. The Role of Epigenetic Change in Autism Spectrum Disorders. Frontiers in Neurology. 2015 05/26. 02/28/received. 04/28/accepted;6:107.
Tamashiro KL, Moran TH. Perinatal environment and its influences on metabolic programming of offspring. Physiol Behav. 2010 Jul 14;100(5):560-6.
Schwartzer JJ, Careaga M, Onore CE, Rushakoff JA, Berman RF, Ashwood P. Maternal immune activation and strain specific interactions in the development of autism-like behaviors in mice. Transl Psychiatry. 2013;3:e240.
Mehta SH, Kerver JM, Sokol RJ, Keating DP, Paneth N. The Association between Maternal Obesity and Neurodevelopmental Outcomes of Offspring. The Journal of Pediatrics. 2014 11//;165(5):891-6.
Sullivan EL, Riper KM, Lockard R, Valleau JC. Maternal high-fat diet programming of the neuroendocrine system and behavior. Horm Behav. 2015 Apr 24.
Bolton JL, Bilbo SD. Developmental programming of brain and behavior by perinatal diet: focus on inflammatory mechanisms. Dialogues in Clinical Neuroscience. 2014;16(3):307-20.
Serotonin and the enteric nervous system may also help explain gastrointestinal alterations in ASD.
Jaiswal P, Mohanakumar KP, Rajamma U. Serotonin mediated immunoregulation and neural functions: Complicity in the aetiology of autism spectrum disorders. Neuroscience & Biobehavioral Reviews. 2015 8//;55(0):413-31.
Dopaminergic dysregulation
Meth-induced DA release
Meth-induced hyperactivity
D1 and D2 mRNA levels
PND21 mice showed no changes in monoamine levels after maternal valproic acid administration on post-conception day 12.5
Hara Y, Takuma K, Takano E, et al. Reduced prefrontal dopaminergic activity in valproic acid-treated mouse autism model. Behavioural Brain Research. 2015 8/1/;289(0):39-47.
Kriete T, Noelle DC. Dopamine and the development of executive dysfunction in autism spectrum disorders. PLoS One. 2015;10(3):e0121605.
Jellinger KA. The Neurochemical Basis of Autism: From Molecules to Minicolumns. European Journal of Neurology. 2011;18(1):e9-e.
Guiard BP, El Mansari M, Blier P. Cross-talk between dopaminergic and noradrenergic systems in the rat ventral tegmental area, locus ceruleus, and dorsal hippocampus. Mol Pharmacol. 2008 Nov;74(5):1463-75.
Average American diet is roughly 33% kcal from fat (CDC; http://www.cdc.gov/nchs/fastats/diet.htm)
Upon extraction, brains were rinsed with ice-cold Hank’s buffer, sliced midsagitally, and half was later frozen over dry ice and coronally sectioned into 500 micron segments in order to obtain brain regions via micropunches.
DOPAC: 3,4-dihydroxyphenylacetic acid
HVA: homovanillic acid
3-MT: 3-methoxytyramine
5-HT: 5-hydroxytryptamine
5-HIAA: 5-hydroxyindoleacetic acid
MHPG: 3-methoxy-4-hydroxyphenylglycol
Critical window since altered connectivity is seen in autism. Furthermore, post-natal day 10 is prior to weaning (PND21); thus, the offspring’s sole nutritional source is via maternal lactation, allowing us to better factor out environmental impacts on our study.
So the question of why we chose post-natal day 10 in the mouse naturally arises. Looking at critical windows in neurodevelopment, significant increases in rates of axonal growth and synaptogenesis occur in the late third trimester of human gestation. This window is integral for physiologic “wiring” of the brain, including structural formation of cortical regions, as well as functional development, as related to levels of NTs, receptor density in post-synaptic targets, and receptor sensitivity.
Vértes PE, Bullmore ET. Annual Research Review: Growth connectomics – the organization and reorganization of brain networks during normal and abnormal development. Journal of Child Psychology and Psychiatry. 2015;56(3):299-320.
Zakharova LA. Cross-regulation in development of neuroendocrine and immune systems. Russ J Dev Biol. 2010 2010/11/01;41(6):347-56.
Sullivan EL, Riper KM, Lockard R, Valleau JC. Maternal high-fat diet programming of the neuroendocrine system and behavior. Horm Behav. 2015 Apr 24.
Herlenius E, Lagercrantz H. Development of neurotransmitter systems during critical periods. Experimental Neurology. 2004 11//;190, Supplement 1(0):8-21.
Workman AD, Charvet CJ, Clancy B, Darlington RB, Finlay BL. Modeling transformations of neurodevelopmental sequences across mammalian species. J Neurosci. 2013 Apr 24;33(17):7368-83.
Monoamine system most affected by maternal HFD: dopaminergic system.
Brain region most affected: ventral hippocampus; least affected: striatum.
Sex-independent increases in DA levels in PFC, dHIPP, vHIPP. Stat. sig in PFC, dHIPP females, trend in vHIPP fema les.
Sex-independent increase in DOPAC in vHIPP – suggests increased DA vHIPP tone at PND10 due to maternal HFD.
MATERNAL HFD EFFECTS:
Sex-independent increased DA levels in the PFC, dHIPP, and vHIPP.
Statistically significant in female PFC and vHIPP.
EFFECTS OF SEX (not shown)
*HVA levels lower in female PFC, higher in female dHIPP.
*Striatal 3-MT levels higher in females.
Both appear to be driven by maternal diet in females (interaction approaching significance).
Maternal HFD leads to disrupted dopaminergic homeostasis in the PND10 mouse, which may relate to ASD-like behaviors involving behavioral dysregulation or hyperactivity.
Female-restricted increases in 5-HT noted in PFC, vHIPP, CER, but specifically not the dHIPP.
Statistical trend for increased 5-HIAA in female PFC, suggests increased serotonergic tone in PFC in female PND10 mice.
MATERNAL HFD EFFECTS:
(i) sex-dependent female-specific increased 5-HT levels.
Statistically significant in female vHIPP, but not the dHIPP*
Statistical trend in female PFC, CER.
(ii) Increased 5-HIAA levels in female PFC (statistically significant).
Suggests increased serotonergic tone in female PND10 PFC.
EFFECTS OF SEX (not shown) – appear to be driven by maternal diet in females.
*5-HT levels higher in female PFC and CER – appear to be driven by diet.
*5-HT levels lower in female dHIPP – statistically and biologically significant.
Maternal HFD leads to disrupted serotonergic homeostasis in the PND10 female mouse, which may relate to ASD-like behaviors involving communication or social deficits.
There were no statistically significant effects of maternal HFD or sex on MHPG levels in PND10 mouse.
Consistent with other studies.
L.-J. Kepser, J. R. Homberg, The neurodevelopmental effects of serotonin: A behavioural perspective. Behavioural Brain Research 277, 3-13 (2015).
Hara Y, Takuma K, Takano E, et al. Reduced prefrontal dopaminergic activity in valproic acid-treated mouse autism model. Behavioural Brain Research. 2015 8/1/;289(0):39-47.
Loke YJ, Hannan AJ, Craig JM. The Role of Epigenetic Change in Autism Spectrum Disorders. Frontiers in Neurology. 2015 05/26. 02/28/received. 04/28/accepted;6:107.
Recall the valproic-acid mouse study previously mentioned, where no differences were found in monoamine levels at PND21.