Genomics of body fat percentage may contribute to sex bias in anorexia nervosa

Hübel, Christopher; Gaspar, Héléna; Coleman, Jonathan R. I.; Finucane, Hilary; Purves, Kirstin; Hanscombe, Ken B.; Prokopenko, Inga; Graff, Mariaelisa; Ngwa, Julius S.; Workalemahu, Tsegaselassie; O’Reilly, Paul F.; Bulik, Cynthia M.; Breen, Gerome

doi:10.1002/ajmg.b.32709

Cited by 95 publications

(115 citation statements)

References 80 publications

Supporting

Mentioning

104

Contrasting

Order By: Relevance

“…Cross-trait analyses for PRSADHD identified an association with tobacco use disorder, which is known to be highly prevalent in individuals with ADHD (32), suggesting that we are capturing some of the genetic risk for the disorder. Likewise, cross-trait analyses for PRSAN showed a negative association with obesity, which aligns with a recent study where the authors suggest the increased liability to AN in females may be due to sex-specific anthropometric and metabolic genetic factors, specifically body fat percentage (33). In our study it is unclear as whether individuals with high PRSAN have a lower propensity for obesity in the absence of an eating disorder, or whether the result is confounded by the presence of an undiagnosed eating disorder.…”

Section: Discussionsupporting

confidence: 89%

Polygenic risk of psychiatric disorders exhibits cross-trait associations in electronic health record data

Kember

Merikangas

et al. 2019

Preprint

View full text Add to dashboard Cite

Objective: Prediction of disease risk is a key component of precision medicine. Common, complex traits such as psychiatric disorders have a complex polygenic architecture making the identification of a single risk predictor difficult. Polygenic risk scores (PRS) denoting the sum of an individual's genetic liability for a disorder are a promising biomarker for psychiatric disorders, but require evaluation in a clinical setting.Methods: We develop PRS for six psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, cross disorder, attention-deficit/hyperactivity disorder, anorexia nervosa) and 17 non-psychiatric traits in over 10,000 individuals from the Penn Medicine Biobank with accompanying electronic health records. We perform phenomewide association analyses to test their association across disease categories.Results: Four of the six psychiatric PRS were associated with their primary phenotypes (odds ratios between 1.2-1.6). Individuals in the highest quintile of risk had between 1.4-2.9 times higher odds of the disorder than the remaining 80% of individuals. Cross-trait associations were identified both within the psychiatric domain and across trait domains.PRS for coronary artery disease and years of education were significantly associated with psychiatric disorders, largely driven by an association with tobacco use disorder.Conclusions: We demonstrate that the genetic architecture of common psychiatric disorders identified in a clinical setting confirms that which has been derived from large consortia. Even though the risk associated is low in this context, these results suggest that as identification of genetic markers proceeds, PRS is a promising approach for prediction of psychiatric disorders and associated conditions in clinical registries.

show abstract

Section: Discussionsupporting

confidence: 89%

Polygenic risk of psychiatric disorders exhibits cross-trait associations in electronic health record data

Kember

Merikangas

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…The relationship between AN and insulin sensitivity should be investigated by euglycemic hyperinsulinemic clamp that showed mixed findings in very small samples (Castillo, Scheen, Jandrain, & Lefèbvre, ; Castillo, Scheen, Lefebvre, & Luyckx, ; Dostálová et al, ; Karczewska‐Kupczewska et al, ; Pannacciulli et al, ; Prioletta et al, ; Zuniga‐Guajardo, Garfinkel, & Zinman, ). This approach is supported by epidemiological associations of AN with type 1 diabetes (Hedman et al, ) and its genetic overlap with fasting insulin (Duncan et al, ), type 2 diabetes (Watson et al, ), and insulin sensitivity (Hübel et al, ).…”

Section: Discussionmentioning

confidence: 99%

Body composition in anorexia nervosa: Meta‐analysis and meta‐regression of cross‐sectional and longitudinal studies

Hübel

Yılmaz

Schaumberg

et al. 2019

Intl J Eating Disorders

Self Cite

View full text Add to dashboard Cite

Objective Clinically, anorexia nervosa (AN) presents with altered body composition. We quantified these alterations and evaluated their relationships with metabolites and hormones in patients with AN longitudinally. Method In accordance with PRISMA guidelines, we conducted 94 meta‐analyses on 62 samples published during 1996–2019, comparing up to 2,319 pretreatment, posttreatment, and weight‐recovered female patients with AN with up to 1,879 controls. Primary outcomes were fat mass, fat‐free mass, body fat percentage, and their regional distribution. Secondary outcomes were bone mineral density, metabolites, and hormones. Meta‐regressions examined relationships among those measures and moderators. Results Pretreatment female patients with AN evidenced 50% lower fat mass (mean difference [MD]: −8.80 kg, 95% CI: −9.81, −7.79, Q = 1.01 × 10−63) and 4.98 kg (95% CI: −5.85, −4.12, Q = 1.99 × 10−28) lower fat‐free mass, with fat mass preferentially stored in the trunk region during early weight restoration (4.2%, 95% CI: −2.1, −6.2, Q = 2.30 × 10−4). While the majority of traits returned to levels seen in healthy controls after weight restoration, fat‐free mass (MD: −1.27 kg, 95% CI: −1.79, −0.75, Q = 5.49 × 10−6) and bone mineral density (MD: −0.10 kg, 95% CI: −0.18, −0.03, Q = 0.01) remained significantly altered. Discussion Body composition is markedly altered in AN, warranting research into these phenotypes as clinical risk or relapse predictors. Notably, the long‐term altered levels of fat‐free mass and bone mineral density suggest that these parameters should be investigated as potential AN trait markers. ResumenObjetivo Clínicamente, la anorexia nervosa (AN) se presenta con alteraciones en la composición corporal. Cuantificamos estas alteraciones y evaluamos longitudinalmente su relación con metabolitos y hormonas en pacientes con AN. Método De acuerdo con las pautas PRISMA, realizamos 94 meta‐análisis en 62 muestras publicadas entre 1996–2019, comparando hasta 2,319 pacientes mujeres en pre‐tratamiento, post‐tratamiento, y recuperadas en base al peso con hasta 1,879 controles. Las principales medidas fueron masa grasa, masa libre de grasa, porcentaje de grasa corporal y su distribución regional. Las medidas secundarias fueron densidad mineral ósea, metabolitos y hormonas. Las meta‐regresiones examinaron las relaciones entre esas medidas y moderadores. Resultados Las pacientes femeninas con AN pre‐tratamiento mostraron un 50% menos de masa grasa (MD: −8.80 kg, CI 95%: −9.81, −7.79, Q = 1.01 × 10–63) y 4.98 kg (CI 95%: −5.85, −4.12, Q = 1.99 × 10–28) menos de masa libre de grasa, con masa grasa preferentemente almacenada en la región del tronco durante la recuperación temprana del peso (4.2%, CI 95%: −2.1, −6.2, Q = 2.30 × 10–4). Aunque la mayoría de los rasgos regresaron a los niveles vistos en los controles sanos después de la restauración del peso, la masa libre de grasa (MD: −1.27 kg, CI 95%: −1.79, −0.75, Q = 5.49 × 10–6) y la densidad mineral ósea (MD: −0.10 kg, CI 95%: −0.18, −0.03, Q = 0.01) perm...

show abstract

“…Of the above identified loci, 17 were reported by GWAS or meta-analysis of DXA-derived lean mass [13, 15, 19]; 104 were reported by a study of electronic impedance measured lean mass in a subset UKB cohort subjects (N=155,961) [20].…”

Section: Resultsmentioning

confidence: 99%

Genome-wide association study of appendicular lean mass in UK Biobank cohort

Pei¹,

Liu

Yang³

et al. 2019

Preprint

View full text Add to dashboard Cite

Lean body mass (LBM), an important physiological measure, has a strong genetic determination. To clarify its genetic basis, a large-scale genome-wide association study (GWAS) of appendicular lean mass (ALM) was conducted in 450,580 UK Biobank subjects. A total of 717 variants (p<5×10−9) from 561 loci were identified, which were replicated across genders (achieving p<5×10−5 in both genders). The identified variants explained ~11% phenotypic variance, accounting for one quarter of the total ~40% GWAS-attributable heritability. The identified variants were enriched in gene sets related to musculoskeletal and connective tissue development. Of interest are several genes, including ADAMTS3, PAM, SMAD3 and MEF2C, that either contain multiple significant variants or serve as the hub genes of the associated gene sets. Polygenic score prediction based on the associated variants was able to distinguish subjects of high from low ALM. Overall, our results offered significant findings on the genetic basis of lean mass through an extraordinarily large sample GWAS. The findings are important to not only lean mass per se but also other complex diseases, such as type 2 diabetes and fracture, as our Mendelian randomization analysis showed that ALM is a protective factor for these two diseases.

show abstract

Genomics of body fat percentage may contribute to sex bias in anorexia nervosa

Cited by 95 publications

References 80 publications

Polygenic risk of psychiatric disorders exhibits cross-trait associations in electronic health record data

Polygenic risk of psychiatric disorders exhibits cross-trait associations in electronic health record data

Body composition in anorexia nervosa: Meta‐analysis and meta‐regression of cross‐sectional and longitudinal studies

Genome-wide association study of appendicular lean mass in UK Biobank cohort

Contact Info

Product

Resources

About