News and Updates

Scientists have identified many reasons why women get breast cancer. However, we don’t understand why, for some women, the risk of breast cancer increases in the decade after they have a baby. Postpartum breast cancer (PPBC) accounts for more than half of breast cancers in women younger than age 45. It is usually a fast-growing cancer that often results in death. Currently, we have no effective ways to prevent, screen, or test younger women for PPBC. In this project, scientists will use electronic health record information along with information from the KP Research Bank to develop risk models for PPBC. This work will be a first step in developing ways to identify and screen women who have a high risk of developing PPBC.

Most doctor visits in the United States end with the patient receiving at least one medication prescription. However, doctors may not have all the information they need to choose the most effective medication and dose for each patient. In this study, scientists will use hundreds of thousands of patients’ medication records from the KP Research Bank to look for patterns in how patients responded to medications. The patterns might be based on factors such as age, gender, race and ethnicity, genetics, lifestyle, and the environment. The goal of this study is to develop tools to help doctors choose the medication and dose that are best for each patient.

Research shows that loneliness and long periods of isolation from other people can shorten the lives of people who have cancer. To ensure physical distancing during the COVID-19 pandemic, Kaiser Permanente temporarily stopped cancer screenings for members. This temporary halt delayed cancer diagnoses and ongoing treatments for some people.

In 2020, the KP Research Bank collected survey information from participants about the pandemic’s effect on their lives. For example, the survey asked if participants lived alone and about any changes in who lived with them. The survey also asked about feelings of loneliness and online social activity.

In this study, scientists will study participants’ answers to these questions to understand how their experiences, including feelings of isolation, affected participants who were and were not receiving cancer treatment during the pandemic. The study will help us better understand how social isolation and loneliness affect people with cancer.

Shoulder pain caused by conditions such as rotator cuff tears, shoulder arthritis, and frozen shoulder affects millions of people each year and is common after age 40. Current treatment includes physical therapy and surgery. The causes of these shoulder conditions are not well understood, and individuals’ genetics may play a role. The purpose of this study is to look at the connection between a person’s genome and shoulder problems. The researchers will use genome-wide association study results from KP Research Bank participants to analyze the genetics of patients with and without shoulder problems. The results from this study may help doctors identify patients who are at risk for conditions that cause shoulder pain so they can improve treatments and outcomes for patients.

The 2019 novel coronavirus (SARS-CoV-2), which causes COVID-19, spread across the world causing a global pandemic. The virus’s high infection rate and the severity of symptoms in older adults and those with underlying conditions have resulted in unprecedented actions across the United States to slow its transmission. These include national emergency declarations and shelter-in-place orders that closed businesses and mandated social distancing. These measures have been successful in slowing the spread of COVID-19, but they have also caused enormous social and economic disruptions, including increases in unemployment and financial strain. The uncertainty associated with the COVID-19 pandemic and social distancing practices may also lead to anxiety and depression. Thus, it is important to understand the direct health effects of the pandemic, as well as its social and behavioral impact. This project aims to 1) characterize the health-impacts of COVID-19 in cancer survivors; 2) identify demographic, household, behavioral, and health history factors associated with severe COVID-19 outcomes in cancer survivors; and 3) evaluate the behavioral, social, and mental health impacts of the COVID-19 pandemic on cancer survivors.

Bloodstream infection (sepsis) is a common cause of death in North America and across the world, but little is known about genetic susceptibility to this infection. We are conducting a series of genetic studies in two separate populations, a Norwegian (https://www.ntnu.edu/) and an American population (KP Research Bank), totaling more than 150,000 people. We are examining millions of single point mutations in the DNA of these individuals, and seeing how they are associated with risk of contracting and dying from a bloodstream infection, along with some common causes of sepsis, such as lower respiratory tract infection, urinary tract infection, and skin infections. We will also look at the genetic risk of bloodstream infection among people with cancer or those undergoing prostate biopsies. If we observe similar patterns in the Norwegian and U.S. populations, we can be more confident that the findings are not by chance. The study is the largest to date on this topic. The knowledge generated from this project may help guide clinical decisions for both doctors and patients, and further personalize follow-up, diagnosis, and treatment in the future.

When a patient first shows signs of severe mental illness (psychotic symptoms), it can be difficult to tell if the symptoms are due to depression, bipolar disorder, or schizophrenia. These similarities can lead to misdiagnosis, improper treatment, and delays in care. As such, there is a need for reliable biological markers that could help predict which patients will go on to develop depression, schizophrenia, bipolar disorder, or not have any further psychiatric symptoms. Such markers would lower patient suffering and potentially improve outcomes. This study is examining the role of mitochondria in individuals with a psychotic disturbance to predict what psychiatric diagnoses they will develop compared to people who are otherwise similar in age, gender, and general health status, but without serious mental illnesses. It is the first study to compare patients with psychotic disturbances who develop schizophrenia, bipolar disorder, and depression to patients who do not develop any severe mental illness. This study will provide preliminary evidence of potential biological markers to help differentiate and understand the underlying biology involved in these conditions.

Time and again, it has been shown that individuals with dementia have a reduced risk of cancer and individuals with cancer have a reduced risk of dementia. It is not clear, however, how the two conditions are related biologically. We propose to study how genetics might influence dementia and cancer in opposite directions. The results have the potential to yield pivotal insights into the underpinnings of the diseases and to inform possible prevention and therapeutic strategies. Such science could provide critical given the substantial effects of dementia and cancer on quality of life and mortality.

The prevalence of lung injury cases associated with e-cigarette or vaping products necessitates rigorous research to understand health outcomes associated with e-cigarette use. This study will examine health care utilization, cardiovascular disease, pulmonary health outcomes, and COVID-19 illness among three groups of KPRB participants: e-cigarette users, smokers who do not use e-cigarettes, and never-smokers. Results from this study will contribute to the scientific literature by describing the population of patients who use e-cigarettes and evaluating the health outcomes associated with e-cigarette use. Patients and KP members will benefit from these findings as their medical providers will be able to provide more information about risks associated with e-cigarette use.

Excess weight puts people at risk for certain cancers, and the number of people who get these cancers is going up, along with the obesity epidemic. Up to half of all women who develop cancer in the lining of the womb or uterus (endometrial cancer) carry excess weight. While Pap smears can find cervical cancer early, we currently do not have good ways to test for endometrial cancer or precancer so it can be found and treated early.

Using Kaiser Permanente’s electronic health record, scientists will look for endometrial precancer or cancer diagnoses and treatment and identify characteristics, such as obesity, that increase the risk of getting this disease. Scientists will use KP Research Bank survey data on lifestyle habits, such as exercise and diet, to see if these habits impact the risk of developing endometrial precancer or cancer. They will also be able to identify which women may benefit the most from endometrial cancer screening to help doctors detect and find changes (precancerous cells) in the lining of the womb or uterus that can be treated before they turn into cancer.

Low back pain and other lumbar spinal disorders cause people more disability than any other health condition. Lumbar spinal disorders are the third leading cause of health care costs. This is in large part caused by spine surgery, including surgery that doesn’t improve a person’s well-being. A major problem with spine care is that doctors don’t know which people with a lumbar spinal disorder are more likely to recover without surgery. The goal of this project is to develop precision medicine approaches that will help Kaiser Permanente members and their health care teams make informed decisions about non-surgical and surgical treatment for lumbar spine disorders. First, scientists will develop models using information from the Kaiser Permanente electronic health record and members’ genetic risk profiles to predict low back pain-related outcomes, including whether or not spine surgery would be a good option. Second, scientists will test the models they develop using separate groups of people to ensure the models are accurate. These findings may ultimately inform development of electronic tools that can be used to help patients and doctors make better decisions when deciding about treatment for lumbar spine disorders.

The coronavirus (COVID-19) caused a global pandemic. Older individuals and those with underlying medical conditions have especially been at a higher risk for hospitalization or death. Communities of color are experiencing disproportionately high death rates from COVID-19. However, most people experience cases that are mild or asymptomatic. Scientists believe that underlying genetic factors contribute to the severity of COVID-19 infection. The purpose of this study is to identify genes that are associated with severe cases of COVID-19 (that result in hospitalization and death) compared to mild cases and those without any symptoms at all.

We hope the results of this study will lead to an understanding of genetic factors associated with COVID-19, and potentially lead to effective treatments of COVID-19 infections.

Nearly half of adults in the U.S. have some kind of cardiovascular disease, including heart attacks and strokes. Statins are medications that lower cholesterol and are proven to be effective in reducing the risk of cardiovascular disease. Over 70 million patients nationwide are recommended to take this medication. There is some evidence that a person’s genetic background could help doctors improve statin prescribing, but this has not been fully studied.

The main goal of this project is to find out if genetic factors can predict how well specific statins work at reducing the risk of cardiovascular disease for people with different genetic backgrounds. The study team will compare cardiovascular health and disease in hundreds of thousands of statin users and nonusers using KP Research Bank health records and genetic data. The results of the study may help further reduce the risk of cardiovascular disease by taking a person’s genetic background into account when prescribing statin medications.

Mammograms used to screen for breast cancer can reduce deaths by making diagnoses earlier but sometimes result in false positives. A false positive result means the test shows the person has changes in breast tissue consistent with breast cancer, but they do not have the disease. False positive results can lead to unnecessary biopsies and overtreatment of small, low-risk cancers that would not otherwise cause harm.

Risk prediction models use a person’s characteristics, like age and family history of breast cancer, to estimate how likely it is they will develop breast cancer. Improved breast cancer risk prediction models make it possible for screening tests to be tailored by a person’s risk level. This would maximize the benefits and minimize the harms of mammogram screening tests.

The goal of this study is to find out if using mammogram screening results and polygenic risk scores (a number that summarizes the effect of many genetic variants) could improve breast cancer risk prediction models.

The goal of this project is to improve the performance of the prostate cancer screening test called prostate-specific antigen (PSA). Men who have an elevated PSA level may get a prostate biopsy. One part of this study is to see if genetic factors can lead to better choices about whether or not a person should have a biopsy. Another part of the study will try to find out if some men who get diagnosed with prostate cancer can have periodic checkups rather than immediately having surgery or radiation. This is important because many prostate cancers are very slow growing and will not lead to complications or death. Having this kind of information could help improve quality of life for men with a new diagnosis of prostate cancer.

Primary open-angle glaucoma (POAG) is a leading cause of permanent blindness. POAG is mainly caused by increased pressure in the eye. This study will look for new genetic factors linked to a person’s risk of POAG and determine how those factors may impact:

• Risk of developing POAG
• Response to eye pressure lowering medications

By using electronic health care records linked to genetic data from the KP Research Bank, researchers will study the clinical care of Kaiser Permanente members who have had vision exams. Researchers expect that this study will help explain the factors related to POAG risk and inform the development of new treatments.

Bariatric surgery is currently the most effective long-term treatment for severe obesity. In this study, researchers are trying to answer the following question: Why do some people not lose weight as expected after bariatric surgery? Using electronic health records with linked genetic data from the KP Research Bank, researchers will study the clinical care of Kaiser Permanente members who have had bariatric surgery. Researchers hope to understand both the genetic and non-genetic factors that contribute to weight loss after bariatric surgery.

It’s estimated that nearly 95 million people around the world get cataracts. Cataracts are usually related to aging and are a leading cause of permanent blindness. Because cataracts are caused by genetic and nongenetic factors, this project will study how both types of factors increase the likelihood that a person will develop cataracts. Scientists will follow the clinical care of nearly 350,000 KP Research Bank members, comparing people who have cataracts to those who don’t. The goal of the project is to better understand why some people are more likely to develop cataracts. These results can help develop better cataract prevention and screening tests.

The number of people who die from breast cancer is much smaller than it was decades ago.  This is for two reasons: 1) Many women get regularly scheduled mammograms. They also get needed follow-up treatment at the early stages of breast cancer when it is easiest to treat. 2) Improved cancer treatments mean fewer people die from breast cancer.

Mammograms find breast cancer at its early stages. However, mammograms sometimes give a “false positive” result. A false positive means that even though the test says the person might have a disease, the person does not have the disease. People who have false positives from mammograms may have extra tests they don’t need, such as surgical biopsies. The extra tests can cause mental and physical discomfort and other harms.

With data from the KP Research Bank, Kaiser Permanente researchers are using “radiomics” to improve the reading of mammograms. Radiomics is a new way to use artificial intelligence and risk prediction to better understand images from tests such as like mammograms, CT (computed tomography) scans, or MRI tests (magnetic resonance imaging).

Based on other results, the researchers expect that this new project will make mammogram results more accurate. This improvement will help reduce false positives and unnecessary tests. The improvements may also lower breast cancer-related deaths.

CMV, human cytomegalovirus, is the most common infection babies can get before they are born. In the United States, about 1 of every 150 to 200 babies are born with congenital CMV (cCMV).  About 1 in 5 of the babies born with cCMV has developmental delays and/or hearing loss. What doctors and researchers don’t currently know is whether babies born with cCMV are also at higher risk of having autism spectrum disorder.

Researchers will study more than 7,000 children born between 2011 and 2019. Some will have cCMV and some will not. These children had mothers who donated blood samples to the KP Research Bank during the first and second trimester of their pregnancies. The researchers will measure antibodies in blood samples to see how cCMV might be linked to developmental disorders, hearing loss, and autism spectrum disorder.