The Interaction of Seasonality, Place of Birth, Genetic Risk and Subsequent Schizophrenia in a High Risk Sample

1983 ◽  
Vol 143 (4) ◽  
pp. 383-388 ◽  
Author(s):  
Ricardo A. Machón ◽  
Sarnoff A. Mednick ◽  
Fini Schulsinger

SummaryBirths occurring in winter months, which are high viral infection months, have been repeatedly shown to produce a slight excess of later-diagnosed schizophrenics. As a result, some researchers have speculated on the possible aetiological effect of viral infections on some forms of schizophrenia. The implications of the viral hypothesis were indirectly tested in the context of an ongoing prospective study of Danish children at high-risk (HR) for schizophrenia. A third-order analysis of variance interaction was hypothesized. Genetically vulnerable individuals, born in winter, in an urban environment (which increases the likelihood of the presence and transmission of viruses) would be more likely, as foetuses or neonates, to have suffered some CNS damage due to the infection; thus they would show higher rates of schizophrenia diagnoses. This hypothesis was supported. The rate of schizophrenia in the HR-urban-winter birth condition reached 23.3 per cent, considerably above population base rates (1 per cent) or rates for the HR subjects (8.9 per cent). Alternative explanations for the results were explored.

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Carly A. Conran ◽  
Zhuqing Shi ◽  
William Kyle Resurreccion ◽  
Rong Na ◽  
Brian T. Helfand ◽  
...  

Abstract Background Genome-wide association studies have identified thousands of disease-associated single nucleotide polymorphisms (SNPs). A subset of these SNPs may be additively combined to generate genetic risk scores (GRSs) that confer risk for a specific disease. Although the clinical validity of GRSs to predict risk of specific diseases has been well established, there is still a great need to determine their clinical utility by applying GRSs in primary care for cancer risk assessment and targeted intervention. Methods This clinical study involved 281 primary care patients without a personal history of breast, prostate or colorectal cancer who were 40–70 years old. DNA was obtained from a pre-existing biobank at NorthShore University HealthSystem. GRSs for colorectal cancer and breast or prostate cancer were calculated and shared with participants through their primary care provider. Additional data was gathered using questionnaires as well as electronic medical record information. A t-test or Chi-square test was applied for comparison of demographic and key clinical variables among different groups. Results The median age of the 281 participants was 58 years and the majority were female (66.6%). One hundred one (36.9%) participants received 2 low risk scores, 99 (35.2%) received 1 low risk and 1 average risk score, 37 (13.2%) received 1 low risk and 1 high risk score, 23 (8.2%) received 2 average risk scores, 21 (7.5%) received 1 average risk and 1 high risk score, and no one received 2 high risk scores. Before receiving GRSs, younger patients and women reported significantly more worry about risk of developing cancer. After receiving GRSs, those who received at least one high GRS reported significantly more worry about developing cancer. There were no significant differences found between gender, age, or GRS with regards to participants’ reported optimism about their future health neither before nor after receiving GRS results. Conclusions Genetic risk scores that quantify an individual’s risk of developing breast, prostate and colorectal cancers as compared with a race-defined population average risk have potential clinical utility as a tool for risk stratification and to guide cancer screening in a primary care setting.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ganna Leonenko ◽  
Emily Baker ◽  
Joshua Stevenson-Hoare ◽  
Annerieke Sierksma ◽  
Mark Fiers ◽  
...  

AbstractPolygenic Risk Scores (PRS) for AD offer unique possibilities for reliable identification of individuals at high and low risk of AD. However, there is little agreement in the field as to what approach should be used for genetic risk score calculations, how to model the effect of APOE, what the optimal p-value threshold (pT) for SNP selection is and how to compare scores between studies and methods. We show that the best prediction accuracy is achieved with a model with two predictors (APOE and PRS excluding APOE region) with pT<0.1 for SNP selection. Prediction accuracy in a sample across different PRS approaches is similar, but individuals’ scores and their associated ranking differ. We show that standardising PRS against the population mean, as opposed to the sample mean, makes the individuals’ scores comparable between studies. Our work highlights the best strategies for polygenic profiling when assessing individuals for AD risk.


Author(s):  
Marianne Vogsen ◽  
Jeanette Dupont Jensen ◽  
Ivar Yannick Christensen ◽  
Oke Gerke ◽  
Anne Marie Bak Jylling ◽  
...  

2009 ◽  
Vol 85 (5) ◽  
pp. 348-353 ◽  
Author(s):  
J M Baeten ◽  
W M Hassan ◽  
V Chohan ◽  
B A Richardson ◽  
K Mandaliya ◽  
...  

2016 ◽  
Vol 247 ◽  
pp. 42-48 ◽  
Author(s):  
Silvia Rigucci ◽  
Giulia Santi ◽  
Valentina Corigliano ◽  
Annamaria Imola ◽  
Camilla Rossi-Espagnet ◽  
...  

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