Impact of pathogenic FBN1 variant types on the development of severe scoliosis in patients with Marfan syndrome

BackgroundAmong the several musculoskeletal manifestations in patients with Marfan syndrome, spinal deformity causes pain and respiratory impairment and is a great hindrance to patients’ daily activities. The present study elucidates the genetic risk factors for the development of severe scoliosis in patients with Marfan syndrome.MethodsWe retrospectively evaluated 278 patients with pathogenic or likely pathogenic FBN1 variants. The patients were divided into those with (n=57) or without (n=221) severe scoliosis. Severe scoliosis was defined as (1) patients undergoing surgery before 50 years of age or (2) patients with a Cobb angle exceeding 50° before 50 years of age. The variants were classified as protein-truncating variants (PTVs), which included variants creating premature termination codons and inframe exon-skipping, or non-PTVs, based on their location and predicted amino acid alterations, and the effect of the FBN1 genotype on the development of severe scoliosis was examined. The impact of location of FBN1 variants on the development of severe scoliosis was also investigated.ResultsUnivariate and multivariate analyses revealed that female sex, PTVs of FBN1 and variants in the neonatal region (exons 25–33) were all independent significant predictive factors for the development of severe scoliosis. Furthermore, these factors were identified as predictors of progression of existing scoliosis into severe state.ConclusionsWe elucidated the genetic risk factors for the development of severe scoliosis in patients with Marfan syndrome. Patients harbouring pathogenic FBN1 variants with these genetic risk factors should be monitored carefully for scoliosis progression.

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Assessment of The Influence of Non-Genetic Risk Factors on The Disease Onset and Progression of Androgenetic Alopecia in Egyptian Males

QJM ◽

10.1093/qjmed/hcab093.002 ◽

2021 ◽

Vol 114 (Supplement_1) ◽

Author(s):

Naziha Hafez Khafagy ◽

Marwa Yassin Soltan ◽

Ahmed Adel Ali Ali

Keyword(s):

Risk Factors ◽

Hair Loss ◽

Genetic Risk ◽

Disease Onset ◽

Genetic Risk Factors ◽

Androgenetic Alopecia ◽

Major Type ◽

Young Males ◽

Potential Risk Factors ◽

The Impact

Abstract Background Androgenetic alopecia (AGA) is a patterned hair loss with multifactorial background including genetic, hormonal as well as environmental and lifestyle-related risk factors. The impact of non-genetic risk factors on the onset and disease progression of androgenetic alopecia in Egyptian males. Objective To explore the potential role of non-genetic risk factors on the disease development and progression of androgenetic alopecia in Egyptian males. Patients and Methods The study included 2000 subjects with and without AGA, during the period from February 2019 to September 2019. The study protocol was approved by faculty of medicine, Ain Sham University, Research ethics committee (FWA 000017585). An informed written consent for participation in this study was obtained from patients and controls before enrollment. One thousand male patients with AGA were recruited in the study. The diagnosis was made via clinical diagnosis, dermatological findings, trichoscopic assessment. Results Our study showed that after skin examination 416 patients had acne and 344 patients had seborrhea, with statistically significant association to AGA cases. Conclusion From our study, it can be concluded that AGA became a major type of hair loss complaint among Egyptian males especially young males. Many potential risk factors were found to be associated with the disease as smoking, stress, obesity, family history, exercise, HTN and unbalanced diet. Avoidance of such risk factors may help improve the disease.

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The impact of age on genetic risk for common diseases

10.1101/2020.07.17.208280 ◽

2020 ◽

Author(s):

Xilin Jiang ◽

Chris Holmes ◽

Gil McVean

Keyword(s):

Risk Factors ◽

Recent Work ◽

Genetic Risk ◽

Genetic Risk Factors ◽

Individual Risk ◽

Uk Biobank ◽

Common Diseases ◽

The Impact ◽

The Relationship ◽

Over Time

AbstractInherited genetic variation contributes to individual risk for many complex diseases and is increasingly being used for predictive patient stratification. Recent work has shown that genetic factors are not equally relevant to human traits across age and other contexts, though the reasons for such variation are not clear. Here, we introduce methods to infer the form of the relationship between genetic risk for disease and age and to test whether all genetic risk factors behave similarly. We use a proportional hazards model within an interval-based censoring methodology to estimate age-varying individual variant contributions to genetic risk for 24 common diseases within the British ancestry subset of UK Biobank, applying a Bayesian clustering approach to group variants by their risk profile over age and permutation tests for age dependency and multiplicity of profiles. We find evidence for age-varying risk profiles in nine diseases, including hypertension, skin cancer, atherosclerotic heart disease, hypothyroidism and calculus of gallbladder, several of which show evidence, albeit weak, for multiple distinct profiles of genetic risk. The predominant pattern shows genetic risk factors having the greatest impact on risk of early disease, with a monotonic decrease over time, at least for the majority of variants although the magnitude and form of the decrease varies among diseases. We show that these patterns cannot be explained by a simple model involving the presence of unobserved covariates such as environmental factors. We discuss possible models that can explain our observations and the implications for genetic risk prediction.Author summaryThe genes we inherit from our parents influence our risk for almost all diseases, from cancer to severe infections. With the explosion of genomic technologies, we are now able to use an individual’s genome to make useful predictions about future disease risk. However, recent work has shown that the predictive value of genetic information varies by context, including age, sex and ethnicity. In this paper we introduce, validate and apply new statistical methods for investigating the relationship between age and genetic risk. These methods allow us to ask questions such as whether risk is constant over time, precisely how risk changes over time and whether all genetic risk factors have similar age profiles. By applying the methods to data from the UK Biobank, a prospective study of 500,000 people, we show that there is a tendency for genetic risk to decline with increasing age. We consider a series of possible explanations for the observation and conclude that there must be processes acting that we are currently unaware of, such as distinct phases of life in which genetic risk manifests itself, or interactions between genes and the environment.

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Identifying Genetic Risk Factors for Diabetic Macular Edema and the Response to Treatment

Journal of Diabetes Research ◽

10.1155/2020/5016916 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Rajya L. Gurung ◽

Liesel M. FitzGerald ◽

Bennet J. McComish ◽

Nitin Verma ◽

Kathryn P. Burdon

Keyword(s):

Risk Factors ◽

Macular Edema ◽

Diabetic Macular Edema ◽

Genetic Risk ◽

Vision Loss ◽

Genetic Risk Factors ◽

Response To Treatment ◽

Diabetic Eye Disease ◽

Genetic And Environmental Factors ◽

The Impact

Diabetic retinopathy (DR) is the most common microvascular complication of diabetes mellitus (DM). DR is complex and the term encompasses several clinical subtypes of diabetic eye disease, including diabetic macular edema (DME), the most frequent cause of central vision loss in DR patients. Both genetic and environmental factors contribute to the pathophysiology of DR and its subtypes. While numerous studies have identified several susceptibility genes for DR, few have investigated the impact of genetics on DME susceptibility. This review will focus on the current literature surrounding genetic risk factors associated with DME. We will also highlight the small number of studies investigating the genetics of response to antivascular endothelial growth factor (anti-VEGF) injection, which is used to treat DME.

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Evidence, and replication thereof, that molecular-genetic and environmental risks for psychosis impact through an affective pathway

Psychological Medicine ◽

10.1017/s0033291720003748 ◽

2020 ◽

pp. 1-13

Author(s):

Jim van Os ◽

Lotta-Katrin Pries ◽

Margreet ten Have ◽

Ron de Graaf ◽

Saskia van Dorsselaer ◽

...

Keyword(s):

Risk Factors ◽

Genetic Risk ◽

Molecular Genetic ◽

Population Sample ◽

Genetic Risk Factors ◽

Schizophrenia Spectrum Disorders ◽

Affective Dysregulation ◽

Delusional Ideation ◽

Schizophrenia Spectrum ◽

The Impact

Abstract Background There is evidence that environmental and genetic risk factors for schizophrenia spectrum disorders are transdiagnostic and mediated in part through a generic pathway of affective dysregulation. Methods We analysed to what degree the impact of schizophrenia polygenic risk (PRS-SZ) and childhood adversity (CA) on psychosis outcomes was contingent on co-presence of affective dysregulation, defined as significant depressive symptoms, in (i) NEMESIS-2 (n = 6646), a representative general population sample, interviewed four times over nine years and (ii) EUGEI (n = 4068) a sample of patients with schizophrenia spectrum disorder, the siblings of these patients and controls. Results The impact of PRS-SZ on psychosis showed significant dependence on co-presence of affective dysregulation in NEMESIS-2 [relative excess risk due to interaction (RERI): 1.01, p = 0.037] and in EUGEI (RERI = 3.39, p = 0.048). This was particularly evident for delusional ideation (NEMESIS-2: RERI = 1.74, p = 0.003; EUGEI: RERI = 4.16, p = 0.019) and not for hallucinatory experiences (NEMESIS-2: RERI = 0.65, p = 0.284; EUGEI: −0.37, p = 0.547). A similar and stronger pattern of results was evident for CA (RERI delusions and hallucinations: NEMESIS-2: 3.02, p < 0.001; EUGEI: 6.44, p < 0.001; RERI delusional ideation: NEMESIS-2: 3.79, p < 0.001; EUGEI: 5.43, p = 0.001; RERI hallucinatory experiences: NEMESIS-2: 2.46, p < 0.001; EUGEI: 0.54, p = 0.465). Conclusions The results, and internal replication, suggest that the effects of known genetic and non-genetic risk factors for psychosis are mediated in part through an affective pathway, from which early states of delusional meaning may arise.

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Non-genetic risk factors for atrial fibrillation are equally important in both young and old age: A nationwide population-based study

European Journal of Preventive Cardiology ◽

10.1177/2047487320915664 ◽

2020 ◽

pp. 204748732091566

Author(s):

Yun Gi Kim ◽

Kyung-Do Han ◽

Jong-Il Choi ◽

Yun Young Choi ◽

Ha Young Choi ◽

...

Keyword(s):

Risk Factors ◽

Atrial Fibrillation ◽

Alcohol Consumption ◽

Genetic Risk ◽

Age Groups ◽

Genetic Risk Factors ◽

Population Based ◽

The Impact ◽

Onset Atrial Fibrillation ◽

New Onset

Aims There are several non-genetic risk factors for new-onset atrial fibrillation, including age, sex, obesity, hypertension, diabetes, and alcohol consumption. However, whether these non-genetic risk factors have equal significance among different age groups is not known. We performed a nationwide population-based analysis to compare the clinical significance of non-genetic risk factors for new-onset atrial fibrillation in various age groups. Methods and results A total of 9,797,409 people without a prior diagnosis of atrial fibrillation who underwent a national health check-up in 2009 were included. During 80,130,090 person-years of follow-up, a total of 196,136 people were diagnosed with new-onset atrial fibrillation. The impact of non-genetic risk factors on new-onset atrial fibrillation was examined in different age groups. Obesity, male sex, heavy alcohol consumption, smoking, hypertension, diabetes and chronic kidney disease were associated with an increased risk of new-onset atrial fibrillation. With minor variations, these risk factors were consistently associated with the risk of new-onset atrial fibrillation among various age groups. Using these risk factors, we created a scoring system to predict future risk of new-onset atrial fibrillation in different age groups. In receiver operating characteristic curve analysis, the predictive value of these risk factors ranged between 0.556 and 0.603, and no significant trends were observed. Conclusions Non-genetic risk factors for new-onset atrial fibrillation may have a similar impact on different age groups. Except for sex, these non-genetic risk factors can be modifiable. Therefore, efforts to control non-genetic risk factors might have relevance for both the young and old.

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The importance of gene–environment interactions in human obesity

Clinical Science ◽

10.1042/cs20160221 ◽

2016 ◽

Vol 130 (18) ◽

pp. 1571-1597 ◽

Cited By ~ 61

Author(s):

Hudson Reddon ◽

Jean-Louis Guéant ◽

David Meyre

Keyword(s):

Risk Factors ◽

Genetic Risk ◽

Environmental Exposures ◽

Genetic Risk Factors ◽

Human Obesity ◽

Methodological Challenges ◽

Gene Environment ◽

The Impact

Current research has identified several environmental exposures that can moderate the impact of genetic risk factors on obesity. This paper reviews these studies (gene–environment interactions) in the obesity field and outlines the methodological challenges of these investigations.

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AWARE: Randomized study of an EMR-based intervention targeting hereditary cancer (CA) risk awareness in peri-op CA patients (pts).

Journal of Clinical Oncology ◽

10.1200/jco.2017.35.15_suppl.e13119 ◽

2017 ◽

Vol 35 (15_suppl) ◽

pp. e13119-e13119

Author(s):

Michael J. Hall ◽

Elizabeth Handorf ◽

Yana Chertock ◽

Cindy A Keleher ◽

Mark Siemon ◽

...

Keyword(s):

Risk Factors ◽

Risk Assessment ◽

Genetic Risk ◽

Perceived Risk ◽

Information Needs ◽

Randomized Study ◽

Genetic Risk Factors ◽

Risk Awareness ◽

The Impact

e13119 Background: Pts having CA surgery have high information needs related to diagnosis, stage, and what caused their CA. Direct EMR access via web portals has grown, and offers a novel means to integrate supplemental health information into the e-chart, such as relevant genetic risk of CA. The AWARE trial (Advancing Web-based Medical Record Access and Risk Evaluation for Cancer Patients) studied the impact of providing personalized pathology (pPATH) and pers/fam history (PFHx) summaries enhanced with information about genetic CA risk and risk assessment. Methods: Peri-op CA pts completed baseline and 3-mo follow-up surveys. Pts randomized to enhanced (E) arm received pPATH & PFHx summaries with embedded tailored info about genetic CA risk and relevant high-risk features. Unenhanced (U) arm got pPATH & PFHx only. Use of summaries and 2 “Genetic risk: Learn more” links was tracked. Outcomes-Primary: awareness, knowledge (of genetic CA risk); Secondary: perceived risk, use of “Learn more” links, intentions/actions toward risk assessment--were stratified by genetic risk factors reported at baseline (0-1, 2+) & use of “Learn more” links. Results: 171 pts consented; men (p = 0.003) & non-White (p = 0.02) were more likely to decline the study. Overall 149 (87%) were randomized & eligible to use AWARE: 109 (73%) logged in, 120 (81%) completed follow-up. Predictors of AWARE use: White race (p < 0.05), sib w/CA (p < 0.05), and use intention (p = 0.005). Reporting 2+ genetic risk factors at baseline predicted use of pPATH, PFHx, and “Learn more” (all p < 0.001). Awareness increased overall (p < 0.002), but between arm changes in primary outcomes were not significant. E arm (vs U) was borderline more likely to seek risk assessment (32% v 18%, p = 0.09), with impact stronger in pts reporting baseline 0-1 (p = 0.035) vs 2+ risk factors (p = 0.7). Among E arm pts who used “Learn more” links, intentions (p = 0.054) & behaviors (p = 0.035) to seek risk assessment increased. Conclusions: AWARE increased genetic risk awareness overall, but primary outcomes were not met. Usage data and secondary outcomes highlight potential for EMR-based interventions to positively impact preventive behaviors toward genetic risk assessment.

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The impact of age on genetic risk for common diseases

PLoS Genetics ◽

10.1371/journal.pgen.1009723 ◽

2021 ◽

Vol 17 (8) ◽

pp. e1009723 ◽

Cited By ~ 1

Author(s):

Xilin Jiang ◽

Chris Holmes ◽

Gil McVean

Keyword(s):

Risk Factors ◽

Relative Risk ◽

Genetic Risk ◽

Proportional Hazards ◽

Proportional Hazards Model ◽

Explanatory Power ◽

Genetic Risk Factors ◽

Individual Risk ◽

Common Diseases ◽

The Impact

Inherited genetic variation contributes to individual risk for many complex diseases and is increasingly being used for predictive patient stratification. Previous work has shown that genetic factors are not equally relevant to human traits across age and other contexts, though the reasons for such variation are not clear. Here, we introduce methods to infer the form of the longitudinal relationship between genetic relative risk for disease and age and to test whether all genetic risk factors behave similarly. We use a proportional hazards model within an interval-based censoring methodology to estimate age-varying individual variant contributions to genetic relative risk for 24 common diseases within the British ancestry subset of UK Biobank, applying a Bayesian clustering approach to group variants by their relative risk profile over age and permutation tests for age dependency and multiplicity of profiles. We find evidence for age-varying relative risk profiles in nine diseases, including hypertension, skin cancer, atherosclerotic heart disease, hypothyroidism and calculus of gallbladder, several of which show evidence, albeit weak, for multiple distinct profiles of genetic relative risk. The predominant pattern shows genetic risk factors having the greatest relative impact on risk of early disease, with a monotonic decrease over time, at least for the majority of variants, although the magnitude and form of the decrease varies among diseases. As a consequence, for diseases where genetic relative risk decreases over age, genetic risk factors have stronger explanatory power among younger populations, compared to older ones. We show that these patterns cannot be explained by a simple model involving the presence of unobserved covariates such as environmental factors. We discuss possible models that can explain our observations and the implications for genetic risk prediction.

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Heritable Genetic Background Alters Survival and Phenotype of Mll-AF9-Induced Leukemias

10.1101/2020.06.13.149310 ◽

2020 ◽

Author(s):

Kira Young ◽

Matthew A. Loberg ◽

Elizabeth Eudy ◽

Logan S. Schwartz ◽

Kristina D. Mujica ◽

...

Keyword(s):

Risk Factors ◽

Fusion Protein ◽

Genetic Risk ◽

Genetic Background ◽

Genetic Risk Factors ◽

Parental Line ◽

Genome Wide Association Studies ◽

Acute Leukemias ◽

F1 Hybrid ◽

The Impact

AbstractThe MLL-AF9 fusion protein occurring as a result of t(9;11) translocation gives rise to pediatric and adult acute leukemias of distinct lineages, including acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), and mixed phenotype acute leukemia (MPAL). The mechanisms underlying how this same fusion protein results in diverse leukemia phenotypes among different individuals is not well understood. Given emerging evidence from genome-wide association studies (GWAS) that genetic risk factors contribute to MLL-rearranged leukemogenesis, here we tested the impact of genetic background on survival and phenotype of a well-characterized Mll-AF9 knockin mouse model. We crossed this model to five distinct inbred strains (129, A/J, C57BL/6, NOD, CAST), and tested their F1 hybrid progeny for dominant genetic effects on Mll-AF9 phenotypes. We discovered that genetic background altered peripheral blood composition, with Mll-AF9 CAST F1 demonstrating significantly increased B lymphocyte frequency while the remainder of the strains exhibited myeloid-biased hematopoiesis, similar to the parental line. Genetic background also impacted overall survival, with Mll-AF9 A/J F1 and Mll-AF9 129 F1 having significantly shorter survival, and Mll-AF9 CAST F1 having longer survival, compared to the parental line. Furthermore, we observed a range of hematologic malignancies, with Mll-AF9 A/J F1, Mll-AF9 129 F1 and Mll-AF9 B6 F1 developing exclusively myeloid cell malignancies (myeloproliferative disorder (MPD) and AML) whereas a subset of Mll-AF9 NOD F1 developed MPAL and Mll-AF9 CAST F1 developed ALL. This study provides a novel in vivo experimental model to evaluate the underlying mechanisms by which MLL-AF9 results in diverse leukemia phenotypes and provides definitive experimental evidence that genetic risk factors contribute to survival and phenotype of MLL-rearranged leukemogenesis.

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Hippocampal Volume Is Smaller In Female Double Carriers Of Two Strongest AD Genetic Risk Factors

Innovation in Aging ◽

10.1093/geroni/igab046.2455 ◽

2021 ◽

Vol 5 (Supplement_1) ◽

pp. 653-653

Author(s):

Svetlana Ukraintseva ◽

Vladimir Popov ◽

Konstantin Arbeev ◽

Hongzhe Duan ◽

Olivia Bagley ◽

...

Keyword(s):

Risk Factors ◽

Genetic Risk ◽

Statistical Significance ◽

Genetic Risk Factors ◽

Hippocampal Volume ◽

Risk Variant ◽

Risk Variants ◽

Independent Effects ◽

The Impact

Abstract Genetic risk factors for Alzheimer’s disease (AD) may facilitate AD-related changes in the brain long before AD clinical manifestation. While APOE4 was linked to a reduced hippocampal volume (HV) in a number of studies, the impact of rs2075650, another polymorphism strongly associated with AD, on HV is less clear. The rs2075650 (in TOMM40) is only in moderate to low LD with APOE4, and may have independent effects on HV or interact with APOE4. We studied associations of rs2075650 (G allele, risk factor for AD), rs429358 (C allele, proxy for APOE4), and their combinations, with right HV measured by MRI, among 10,738 women and 9,775 men aged 60-75, from UK Biobank. We found that right HV was significantly (p<0.02) smaller in women who carry both AD risk variants (rs2075650(G) and rs429358(C)), than in non-carriers of both of these variants, while having only one risk variant (G or C) didn’t clearly affect HV. The studied associations didn’t reach statistical significance in men. Our results suggest that rs2075650(G) and rs429358(C) may contribute synergistically to a reduction in hippocampus volume, in females only, and support the role of interactions between genetic risk factors for AD in sex differences in preclinical biomarkers of AD pathology.

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