scholarly journals The genomic health of ancient hominins

2017 ◽  
Author(s):  
Ali J. Berens ◽  
Taylor L. Cooper ◽  
Joseph Lachance
Keyword(s):  
Genetic Risk ◽  
Full Range ◽  
Genetic Load ◽  
Hereditary Disease ◽  
Risk Scores ◽  
Hunter Gatherers ◽  
Genetic Risk Scores ◽  
Risk Alleles ◽  
Disease Risks ◽  
Tyrolean Iceman

AbstractThe genomes of ancient humans, Neandertals, and Denisovans contain many alleles that influence disease risks. Using genotypes at 3180 disease-associated loci, we estimated the disease burden of 147 ancient genomes. After correcting for missing data, genetic risk scores were generated for nine disease categories and the set of all combined diseases. These genetic risk scores were used to examine the effects of different types of subsistence, geography, and sample age on the number of risk alleles in each ancient genome. On a broad scale, hereditary disease risks are similar for ancient hominins and modern-day humans, and the GRS percentiles of ancient individuals span the full range of what is observed in present day individuals. In addition, there is evidence that ancient pastoralists may have had healthier genomes than hunter-gatherers and agriculturalists. We also observed a temporal trend whereby genomes from the recent past are more likely to be healthier than genomes from the deep past. This calls into question the idea that modern lifestyles have caused genetic load to increase over time. Focusing on individual genomes, we find that the overall genomic health of the Altai Neandertal is worse than 97% of present day humans and that Ötzi the Tyrolean Iceman had a genetic predisposition to gastrointestinal and cardiovascular diseases. As demonstrated by this work, ancient genomes afford us new opportunities to diagnose past human health, which has previously been limited by the quality and completeness of remains.

Has the time come to integrate genetic risk scores into clinical practice?

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
F.V Moniz Mendonca ◽  
M.I Mendonca ◽  
A Pereira ◽  
J Monteiro ◽  
J Sousa ◽  
...  
Keyword(s):  
Risk Factors ◽  
Clinical Practice ◽  
Genetic Variants ◽  
Genetic Risk ◽  
Odds Ratio ◽  
Risk Scores ◽  
Cumulative Number ◽  
Genetic Risk Scores ◽  
Risk Alleles ◽  
Cad Risk

Abstract Background The risk for Coronary Artery Disease (CAD) is determined by both genetic and environmental factors, as well as by the interaction between them. It is estimated that genetic factors could account for 40% to 55% of the existing variability among the population (inheritability). Therefore, some authors have advised that it is time we integrated genetic risk scores into clinical practice. Aim The aim of this study was to evaluate the magnitude of the association between an additive genetic risk score (aGRS) and CAD based on the cumulative number of risk alleles in these variants, and to estimate whether their use is valuable in clinical practice. Methods A case-control study was performed in a Portuguese population. We enrolled 3120 participants, of whom 1687 were CAD patients and 1433 were normal controls. Controls were paired to cases with respect to gender and age. 33 genetic variants known to be associated with CAD were selected, and an aGRS was calculated for each individual. The aGRS was further subdivided into deciles groups, in order to estimate the CAD risk in each decile, defined by the number of risk alleles. The magnitude of the risk (odds ratio) was calculated for each group by multiple logistic regression using the 5th decile as the reference group (median). In order to evaluate the ability of the aGRS to discriminate susceptibility to CAD, two genetic models were performed, the first with traditional risk factors (TRF) and second with TRF plus aGRS. The AUC of the two ROC curves was calculated. Results A higher prevalence of cases over controls became apparent from the 6th decile of the aGRS, reflecting the higher number of risk alleles present (see figure). The difference in CAD risk was only significant from the 6th decile, increasing gradually until the 10th decile. The odds ratio (OR) for the last decile related to 5th decile (median) was 1.87 (95% CI:1.36–2.56; p<0.0001). The first model yielded an AUC=0.738 (95% CI:0.720–0.755) and the second model was slightly more discriminative for CAD risk (AUC=0.748; 95% CI:0.730–0.765). The DeLong test was significant (p=0.0002). Conclusion Adding an aGRS to the non-genetic risk factors resulted in a modest improvement in the ability to discriminate the risk of CAD. Such improvement, even if statistically significant, does not appear to be of real value in clinical practice yet. We anticipate that with the development of further knowledge about different SNPs and their complex interactions, and with the inclusion of rare genetic variants, genetic risk scores will be better suited for use in a clinical setting. Funding Acknowledgement Type of funding source: None

scholarly journals Multiple SNP testing improves risk prediction of first venous thrombosis

Blood ◽  
2012 ◽  
Vol 120 (3) ◽  
pp. 656-663 ◽  
Author(s):  
Hugoline G. de Haan ◽  
Irene D. Bezemer ◽  
Carine J. M. Doggen ◽  
Saskia Le Cessie ◽  
Pieter H. Reitsma ◽  
...  
Keyword(s):  
Venous Thrombosis ◽  
Risk Prediction ◽  
Genetic Risk ◽  
Risk Model ◽  
Cost Effective ◽  
Risk Scores ◽  
Nucleotide Polymorphisms ◽  
Risk Models ◽  
Genetic Risk Scores ◽  
Risk Alleles

Abstract There are no risk models available yet that accurately predict a person's risk for developing venous thrombosis. Our aim was therefore to explore whether inclusion of established thrombosis-associated single nucleotide polymorphisms (SNPs) in a venous thrombosis risk model improves the risk prediction. We calculated genetic risk scores by counting risk-increasing alleles from 31 venous thrombosis-associated SNPs for subjects of a large case-control study, including 2712 patients and 4634 controls (Multiple Environmental and Genetic Assessment). Genetic risk scores based on all 31 SNPs or on the 5 most strongly associated SNPs performed similarly (areas under receiver-operating characteristic curves [AUCs] of 0.70 and 0.69, respectively). For the 5-SNP risk score, the odds ratios for venous thrombosis ranged from 0.37 (95% confidence interval [CI], 0.25-0.53) for persons with 0 risk alleles to 7.48 (95% CI, 4.49-12.46) for persons with more than or equal to 6 risk alleles. The AUC of a risk model based on known nongenetic risk factors was 0.77 (95% CI, 0.76-0.78). Combining the nongenetic and genetic risk models improved the AUC to 0.82 (95% CI, 0.81-0.83), indicating good diagnostic accuracy. To become clinically useful, subgroups of high-risk persons must be identified in whom genetic profiling will also be cost-effective.

scholarly journals Relationship between Genetic Risk and Age of Diagnosis of Systemic Lupus Erythematosus

2020 ◽  
pp. jrheum.200002
Author(s):  
Daniela Dominguez ◽  
Sylvia Kamphuis ◽  
Joseph Beyene ◽  
Joan Wither ◽  
John B. Harley ◽  
...  
Keyword(s):  
Risk Score ◽  
Lupus Erythematosus ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Ancestral Population ◽  
Childhood Onset ◽  
Genetic Risk Scores ◽  
Risk Alleles ◽  
Age Of Diagnosis

Objective Specific risk alleles for childhood-onset SLE (cSLE) versus adult-onset SLE (aSLE) patients have not been identified. The aims of this study were to determine if: 1) There is an association between non-HLA-related genetic risk score (GRS) and age of SLE diagnosis; and if 2) There is an association between HLA-related genetic risk score and age of SLE diagnosis. Methods Genomic DNA was obtained from 2,001 multi-ethnic patients and genotyped using the Immunochip. Following quality control, genetic risk counting (GRCS), weighted (GRWS) and standardized counting (GRSCS) and standardized weighted (GRSWS) scores were calculated based on independent SNPs from validated SLE-loci. Scores were analyzed in a regression model and adjusted by sex and ancestral population. Results The analysed cohort consisted of 1,540 patients: 1,351 females and 189 males (675 cSLE and 865 aSLE). There were significant negative associations with age of SLE diagnosis p=0.011 and r2=0.175 for GRWS, p=0.008 and r2=0.178 for GRSCS, p=0.002 and r2=0.176 for GRSWS for all non-HLA genetic risk scores (higher GRS the lower the age of diagnosis.) All HLA genetic risk scores showed significant positive associations with age of diagnosis p=0.049 and r2=0.176 for GRCS, p=0.022 and r2=0.176 for GRWS, p=0.022 and r2=0.176 for GRSCS, p=0.011 and r2=0.177 for GRSWS: higher genetic scores correlated with higher age of diagnosis. Conclusion Our data suggested that there is a linear relationship between genetic risk and age of SLE diagnosis and that HLA and non-HLA genetic risk scores are associated with age of diagnosis in opposite directions.

scholarly journals Assessing the clinical utility of genetic risk scores for targeted cancer screening

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Carly A. Conran ◽  
Zhuqing Shi ◽  
William Kyle Resurreccion ◽  
Rong Na ◽  
Brian T. Helfand ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Primary Care ◽  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Clinical Utility ◽  
Low Risk ◽  
Risk Scores ◽  
Average Risk ◽  
Genetic Risk Scores

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.

Predictive Value of Genetic Risk Scores in the Development of Colorectal Adenomas

2021 ◽  
Author(s):  
Carla J. Gargallo-Puyuelo ◽  
Rocío Aznar-Gimeno ◽  
Patricia Carrera-Lasfuentes ◽  
Ángel Lanas ◽  
Ángel Ferrández ◽  
...  
Keyword(s):  
Predictive Value ◽  
Genetic Risk ◽  
Colorectal Adenomas ◽  
Risk Scores ◽  
Genetic Risk Scores

scholarly journals The patterns of family genetic risk scores for eleven major psychiatric and substance use disorders in a Swedish national sample

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kenneth S. Kendler ◽  
Henrik Ohlsson ◽  
Jan Sundquist ◽  
Kristina Sundquist
Keyword(s):  
Genetic Risk ◽  
Molecular Genetic ◽  
National Sample ◽  
Autism Spectrum ◽  
Risk Scores ◽  
Pedigree Data ◽  
Obsessive Compulsive ◽  
Swedish Population ◽  
Compulsive Disorder ◽  
Genetic Risk Scores

AbstractTo clarify the structure of genetic risks for 11 major psychiatric disorders, we calculated, from morbidity risks for disorders in 1st–5th degree relatives controlling for cohabitation effects, in the Swedish population born between 1932 and 1995 (n = 5,830,014), the family genetic risk scores (FGRS) for major depression (MD), anxiety disorders (AD), obsessive-compulsive disorder (OCD), bipolar disorder (BD), schizophrenia (SZ), bulimia (BUL), anorexia nervosa (AN), alcohol use disorder (AUD), drug use disorder (DUD), ADHD, and autism-spectrum disorder (ASD). For all affected individuals, we calculated their mean standardized FGRS for each disorder. The patterns of FGRS were quite similar for MD and AD, and for AUD and DUD, but substantially less similar for BUL and AN, BD and SZ, and ADHD and ASD. While OCD had high levels of FGRS for MD and AD, the overall FGRS profile differed considerably from MD and AD. ADHD FGRS scores were substantially elevated in AUD and DUD. FGRS scores for BD, OCD, AN, ASD, ADHD, and especially SZ were relatively disorder-specific while genetic risk for MD and AD had more generalized effects. The levels of FGRS for BMI, coronary artery disease, and educational attainment across our disorders replicated prior associations found using molecular genetic methods. All diagnostic categories examined had elevated FGRS for many disorders producing, for each condition, an informative FGRS profile. Using a novel method which approximates, from pedigree data, aggregate genetic risk, we have replicated and extended prior insights into the structure of genetic risk factors for key psychiatric illnesses.

IC-P-045: Weighted and unweighted genetic risk scores are associated with longitudinal cortical thinning of hippocampal complex subregions

2015 ◽  
Vol 11 (7S_Part_1) ◽  
pp. P38-P38
Author(s):  
Theresa M. Harrison ◽  
Edward P. Lau ◽  
Zanjbeel Mahmood ◽  
Alison C. Burggren ◽  
Gary W. Small ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Risk Scores ◽  
Cortical Thinning ◽  
Genetic Risk Scores ◽  
Hippocampal Complex

scholarly journals Circadian clock-related genetic risk scores and risk of placental abruption

Placenta ◽  
2015 ◽  
Vol 36 (12) ◽  
pp. 1480-1486 ◽  
Author(s):  
Chunfang Qiu ◽  
Bizu Gelaye ◽  
Marie Denis ◽  
Mahlet G. Tadesse ◽  
Miguel Angel Luque Fernandez ◽  
...  
Keyword(s):  
Circadian Clock ◽  
Genetic Risk ◽  
Placental Abruption ◽  
Risk Scores ◽  
Genetic Risk Scores

scholarly journals Evaluating the discriminative power of multi-trait genetic risk scores for type 2 diabetes in a northern Swedish population

Diabetologia ◽  
2010 ◽  
Vol 53 (10) ◽  
pp. 2155-2162 ◽  
Author(s):  
B. Fontaine-Bisson ◽  
◽  
F. Renström ◽  
O. Rolandsson ◽  
F. Payne ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Genetic Risk ◽  
Risk Scores ◽  
Discriminative Power ◽  
Swedish Population ◽  
Genetic Risk Scores
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