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“Runs in the family” is not a diagnosis- Over the past 10 years, we have heard from thousands of people who have heart disease or had a stroke caused by an inherited cholesterol disorder. Unfortunately, they did not learn of their genetic condition until it was too late. The damage was done. They were told that heart disease or high cholesterol “runs in the family” but were never given the name of the genetic cause that leads to so much heartache across generations. We believe families deserve a diagnosis so they can get the care they deserve. That is why we have launched this campaign. We hope you will join us to help reach people who have never heard of FH or elevated Lipoprotein(a).

Polygenic risk scores (PRSs) derived from genotype data and family history (FH) of disease provide valuable information for predicting disease risk, but PRSs perform poorly when applied to diverse populations. Here, we explore methods for combining both types of information (PRS-FH) in UK Biobank data. We evaluated PRS, FH, and PRS-FH using liability-scale R2, primarily focusing on 3 well-powered diseases (type 2 diabetes, hypertension, and depression). PRS attained average prediction R2s of 5.8%, 4.0%, and 0.53% in non-British Europeans, South Asians, and Africans, confirming poor cross-population transferability. In contrast, PRS-FH attained average prediction R2s of 13%, 12%, and 10%, respectively, representing a large improvement in Europeans and an extremely large improvement in Africans. In conclusion, including family history improves the accuracy of polygenic risk scores, particularly in diverse populations.

This review explores the FH tools currently available for PC and evaluates their clinical performance.Five databases were systematically searched until May 2021. Identified tools were evaluated on the following criteria: time-to-complete, integration with electronic health record (EMR) systems, patient administration, risk-assessment ability, evidence-based management recommendations, analytical and clinical validity and clinical utility.We identified 26?PC FH tools. Analytical and clinical validity was poorly reported and agreement between FH and gold standard was commonly inadequately reported and assessed. Sensitivity was acceptable; specificity was found in half of the reviewed tools to be poor. Most reviewed tools showed a capacity to successfully identify individuals with increased risk of disease (6.2-84.6% of high and/or moderate or increased risk individuals).Despite the potential of FH tools to improve risk stratification of patients in PC, clinical performance of current tools remains limited as well as their integration in EMR systems. Twenty-one FH tools are designed to be self-administered by patients.

Kidney diseases are a leading cause of death in the United States. About 37 million US adults are estimated to have CKD, and most are undiagnosed. 40% of people with severely reduced kidney function (not on dialysis) are not aware of having CKD. Talk to your doctor about getting tested if you have any of these risk factors: Diabetes, High blood pressure, Heart disease, Family history of CKD, Obesity.

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