Latest news with #FredHutchinsonCancerResearchCenter
India Today
5 days ago
- Health
- India Today
Tight bras don't cause cancer, but they're not completely risk-free
Tight bra? Underwire digging in? Wearing it all day and night? If you've ever paused mid-Instagram scroll or heard an aunt whisper, 'You know, wearing that too long can give you cancer,' you're not alone. The idea that bras especially underwire ones can cause breast cancer has lingered like a bad rumour since the 1990s. And while the claim sounds serious enough to spark panic, doctors and researchers say it's simply not said, if your bra is leaving red marks, shoulder dents, or feels like a daily battle with elastic, your body is trying to tell you something but it's not about cancer. From back pain to circulation issues, wearing the wrong size or type of bra can cause plenty of problems but not the one everyone fears the DID THIS MYTH COME FROM?The roots of the bra-cancer myth can be traced back to a 1995 book titled Dressed to Kill by Sydney Ross Singer and Soma Grismaijer. The authors speculated that bras especially underwire bras could obstruct lymphatic flow, thereby "trapping toxins" in breast tissue and leading to cancer. It was a hypothesis, not a scientific study. But the theory spread like wildfire, despite having no basis in medical research. Over time, the idea embedded itself into public consciousness, amplified by social media and anecdotal 'evidence' that lacked scientific RESEARCH ACTUALLY SAYSIn 2014, the Fred Hutchinson Cancer Research Center in Seattle conducted a large-scale, population-based study to examine this very issue. The study, published in the journal Cancer Epidemiology, Biomarkers & Prevention, involved over 1,500 women, both with and without breast RESULTS?There was no link between wearing bras regardless of type, duration, or tightness and an increased risk of breast cancer. Dr. Lu Chen, the lead author of the study, concluded: 'Our study found no evidence that wearing a bra increases breast cancer risk among postmenopausal women.'This aligns with the stance of globally trusted institutions:The American Cancer Society: 'There is no scientifically valid study that shows wearing bras of any type causes breast cancer.' The National Cancer Institute and the Cancer Council of Australia echo the same: No link. No risk. No WEIGH INDr. Therese Bevers, Medical Director at MD Anderson Cancer Center, is direct in her assessment: 'We don't have any evidence to support that underwire bras cause breast cancer cancer is not caused by a wire pinching or poking you anywhere.'Dr. Homayoon Sanati, a breast cancer specialist at MemorialCare Breast Center, also finds the myth implausible: 'Most of the breast cancers we diagnose occur in the upper outer quadrant of the breast, far away from where an underwire rests. If bras were causing blockages that led to cancer, the distribution of tumors would look very different.'WHY THIS MYTH PERSISTSadvertisementSo if there's no evidence, why does the myth live on?Some believe it's tied to the discomfort many women experience with ill-fitting bras. When something feels painful or unnatural, it's easy to associate it with harm. Add in a distrust of the medical establishment or fear of cancer, and the rumor finds fertile ground. Additionally, misinformation spreads faster than scientific nuance especially WEARING THE WRONG BRA CAN DO'Wearing a tight or ill-fitting bra won't give you cancer—but it can certainly give you chronic neck and back pain,' says Dr. Priya Ahuja, senior gynecologist at Bloom Women's Clinic. 'I see women with deep shoulder grooves and posture issues all because their bra isn't giving the right support.' A well-fitting bra is about comfort and support not disease prevention or REAL RISK FACTORS FOR BREAST CANCERRather than fearing your lingerie drawer, experts recommend focusing on these proven risk factors:Age and family historyBRCA1/BRCA2 gene mutationsEarly menstruation or late menopauseObesity and sedentary lifestyleAlcohol consumptionHormonal therapyCOMFORT OVER CANCERBras, underwire or not, are not the enemy. If you're wearing a bra that fits well and makes you feel good keep it. If it digs into your skin, causes discomfort, or feels too tight, it's time to get measured and switch it out—not because of cancer, but because you deserve better with all health-related concerns, it's best to turn to science and trusted medical professionals not whispers in WhatsApp groups or decades-old conspiracy theories.- Ends
The Hindu
17-05-2025
- Health
- The Hindu
How your genes interact with your environment changes your disease risk − new research counts the ways
Sitting in my doctor's examination room, I was surprised when she told me, 'Genetics don't really matter for chronic disease.' Rather, she continued, 'A person's lifestyle, what they eat, and how much they exercise, determine whether they get heart disease.' As a researcher who studies the genetics of disease, I don't fully disagree – lifestyle factors play a large role in determining who gets a disease and who doesn't. But they are far from the entire story. Since scientists mapped out the human genome in 2003, researchers have learned that genetics also play a large role in a person's disease risk. Studies that focus on estimating disease heritability – that is, how much genetic differences explain differences in disease risk – usually attribute a substantial fraction of disease variation to genetics. Mutations across the entire genome seem to play a role in diseases such as Type 2 diabetes, which is about 17% heritable, and schizophrenia, which is about 80% heritable. In contrast to diseases such as Tay-Sachs or cystic fibrosis, where mutations in a single gene cause a disease, chronic diseases tend to be polygenic, meaning they're influenced by multiple mutations at many genes across the whole genome. Every complex disease has both genetic and environmental risk factors. Most researchers study these factors separately because of technical challenges and a lack of large, uniform datasets. Although some have devised techniques to overcome these challenges, they haven't yet been applied to a comprehensive set of diseases and environmental exposures. In our recently published research, my colleague Alkes Price and I developed tools to leverage newly available datasets to quantify the joint effects that genetic and environmental risk factors have on the biology underlying disease. Aspirin, genetics and colon cancer To illustrate the effect gene-environment interactions have on disease, let's consider the example of aspirin use and colon cancer. In 2001, researchers at the Fred Hutchinson Cancer Research Center were studying how regularly taking aspirin decreased the risk of colon cancer. They wondered whether genetic mutations that slowed down how quickly the body broke down aspirin – meaning aspirin levels in the body would stay high longer – might increase the drug's protective effect against colon cancer. They were right: Only patients with slow aspirin metabolism had a decreased risk of colon cancer, indicating that the effectiveness of a drug can depend on a person's genetics. This raises the question of how genetics and different combinations of environmental exposures, such as the medications a patient is taking, can affect a person's disease risk and how effective a treatment will be for them. How many cases of genetic variations directly influencing a drug's effectiveness are there? The gene-environment interaction of colon cancer and aspirin is unusual. It involves a mutation at a single location in the genome that has a big effect on colon cancer risk. The past 25 years of human genetics have shown researchers that these sorts of large-effect mutations are rare. For example, an analysis found that the median effect of a genetic variant on height is only 0.14 millimeters. Instead, there are usually hundreds of variations that each have small but cumulative effects on a person's disease risk, making them hard to find. How could researchers detect these small gene-environment interactions across hundreds of spots in the genome? Polygenic gene-environment interactions We started by looking for cases where genetic variants across the genome showed different effects on a person's biology in different environments. Rather than trying to detect the small effects of each genetic variant one at a time, we aggregated data across the entire genome to turn these small individual effects into a large, genome-wide effect. Using data from the UK Biobank – a large database containing genetic and health data from about 500,000 people – we estimated the influence of millions of genetic variants on 33 complex traits and diseases, such as height and asthma. We grouped people based on environmental exposures such as air pollution, cigarette smoking and dietary patterns. Finally, we developed statistical tests to study how the effects of genetics on disease risk and biomarker levels varied with these exposures. We found three types of gene-environment interactions. First, we found 19 pairs of complex traits and environmental exposures that are influenced by genetic variants across the genome. For example, the effect of genetics on white blood cell levels in the body differed between smokers and nonsmokers. When we compared the effects of genetic mutations between the two groups, the strength of gene-environment interaction suggested that smoking changes the way genetics influence white blood cell counts. Second, we looked for cases where the heritability of a trait varies depending on the environment. In other words, rather than some genetic variants having different effects in different environments, all of them are made stronger in some environments. For example, we found that the heritability of body mass index – the ratio of weight to height – increased by 5% for the most active people. This means genetics plays a larger role in BMI the more active you are. We found 28 such trait-environment pairs, including HDL cholesterol levels and alcohol consumption, as well as neuroticism and self-reported sleeplessness. Third, we looked for a type of gene-environment interaction called proportional or joint amplification. Here, genetic effects grow with increased environmental exposures, and vice versa. This results in a relatively equal balance of genetic and environmental effects on a trait. For example, as self-reported time spent watching television increased, both genetic and environmental variance increased for a person's waist-to-hip ratio. This likely reflects the influence of other behaviors related to time spent watching television, such as decreased physical exercise. We found 15 such trait-environment pairs, including lung capacity and smoking, and glucose levels and alcohol consumption. We also looked for cases where biological sex, instead of environmental exposures, influenced interactions with genes. Previous work had shown evidence of these gene-by-sexinteractions, and we found additional examples of the effects of biological sex on all three types of gene-environment interactions. For example, we found that neuroticism had genetic effects that varied across sex. Finally, we also found that multiple types of gene-environment interactions can affect the same trait. For example, the effects of genetics on systolic blood pressure varied by sex, indicating that some genetic variants have different effects in men and women. New gene-environment models How do we make sense of these distinct types of gene-environment interactions? We argue that they can help researchers better understand the underlying biological mechanisms that lead from genetic and environmental risks to disease, and how genetic variation leads to differences in disease risk between people. Genes related to the same function work together in a unit called a pathway. For example, we can say that genes involved in making heme – the component of red blood cells that carries oxygen – are collectively part of the heme synthesis pathway. The resulting amounts of heme circulating in the body influence other biological processes, including ones that could lead to the development of anemia and cancer. Our model suggests that environmental exposures modify different parts of these pathways, which may explain why we saw different types of gene-environment interactions. In the future, these findings could lead to treatments that are more personalised based on a person's genome. For example, clinicians might one day be able to tell whether someone is more likely to decrease their risk of heart disease by taking weight loss drugs or by exercising. Our results show how studying gene-environment interactions can tell researchers not only about which genetic and environmental factors increase your risk of disease, but also what goes wrong in the body where. (Arun Durvasula is assistant professor of population and public health sciences, University of Southern California. Email: (This article is republished from The Conversation under a Creative Commons license. Read the original article here)
Yahoo
14-05-2025
- Health
- Yahoo
How your genes interact with your environment changes your disease risk − new research counts the ways
Sitting in my doctor's examination room, I was surprised when she told me, 'Genetics don't really matter for chronic disease.' Rather, she continued, 'A person's lifestyle, what they eat, and how much they exercise, determine whether they get heart disease.' As a researcher who studies the genetics of disease, I don't fully disagree – lifestyle factors play a large role in determining who gets a disease and who doesn't. But they are far from the entire story. Since scientists mapped out the human genome in 2003, researchers have learned that genetics also play a large role in a person's disease risk. Studies that focus on estimating disease heritability – that is, how much genetic differences explain differences in disease risk – usually attribute a substantial fraction of disease variation to genetics. Mutations across the entire genome seem to play a role in diseases such as Type 2 diabetes, which is about 17% heritable, and schizophrenia, which is about 80% heritable. In contrast to diseases such as Tay-Sachs or cystic fibrosis, where mutations in a single gene cause a disease, chronic diseases tend to be polygenic, meaning they're influenced by multiple mutations at many genes across the whole genome. Every complex disease has both genetic and environmental risk factors. Most researchers study these factors separately because of technical challenges and a lack of large, uniform datasets. Although some have devised techniques to overcome these challenges, they haven't yet been applied to a comprehensive set of diseases and environmental exposures. In our recently published research, my colleague Alkes Price and I developed tools to leverage newly available datasets to quantify the joint effects that genetic and environmental risk factors have on the biology underlying disease. To illustrate the effect gene-environment interactions have on disease, let's consider the example of aspirin use and colon cancer. In 2001, researchers at the Fred Hutchinson Cancer Research Center were studying how regularly taking aspirin decreased the risk of colon cancer. They wondered whether genetic mutations that slowed down how quickly the body broke down aspirin – meaning aspirin levels in the body would stay high longer – might increase the drug's protective effect against colon cancer. They were right: Only patients with slow aspirin metabolism had a decreased risk of colon cancer, indicating that the effectiveness of a drug can depend on a person's genetics. This raises the question of how genetics and different combinations of environmental exposures, such as the medications a patient is taking, can affect a person's disease risk and how effective a treatment will be for them. How many cases of genetic variations directly influencing a drug's effectiveness are there? The gene-environment interaction of colon cancer and aspirin is unusual. It involves a mutation at a single location in the genome that has a big effect on colon cancer risk. The past 25 years of human genetics have shown researchers that these sorts of large-effect mutations are rare. For example, an analysis found that the median effect of a genetic variant on height is only 0.14 millimeters. Instead, there are usually hundreds of variations that each have small but cumulative effects on a person's disease risk, making them hard to find. How could researchers detect these small gene-environment interactions across hundreds of spots in the genome? We started by looking for cases where genetic variants across the genome showed different effects on a person's biology in different environments. Rather than trying to detect the small effects of each genetic variant one at a time, we aggregated data across the entire genome to turn these small individual effects into a large, genome-wide effect. Using data from the UK Biobank – a large database containing genetic and health data from about 500,000 people – we estimated the influence of millions of genetic variants on 33 complex traits and diseases, such as height and asthma. We grouped people based on environmental exposures such as air pollution, cigarette smoking and dietary patterns. Finally, we developed statistical tests to study how the effects of genetics on disease risk and biomarker levels varied with these exposures. We found three types of gene-environment interactions. First, we found 19 pairs of complex traits and environmental exposures that are influenced by genetic variants across the genome. For example, the effect of genetics on white blood cell levels in the body differed between smokers and nonsmokers. When we compared the effects of genetic mutations between the two groups, the strength of gene-environment interaction suggested that smoking changes the way genetics influence white blood cell counts. Second, we looked for cases where the heritability of a trait varies depending on the environment. In other words, rather than some genetic variants having different effects in different environments, all of them are made stronger in some environments. For example, we found that the heritability of body mass index – the ratio of weight to height – increased by 5% for the most active people. This means genetics plays a larger role in BMI the more active you are. We found 28 such trait-environment pairs, including HDL cholesterol levels and alcohol consumption, as well as neuroticism and self-reported sleeplessness. Third, we looked for a type of gene-environment interaction called proportional or joint amplification. Here, genetic effects grow with increased environmental exposures, and vice versa. This results in a relatively equal balance of genetic and environmental effects on a trait. For example, as self-reported time spent watching television increased, both genetic and environmental variance increased for a person's waist-to-hip ratio. This likely reflects the influence of other behaviors related to time spent watching television, such as decreased physical exercise. We found 15 such trait-environment pairs, including lung capacity and smoking, and glucose levels and alcohol consumption. We also looked for cases where biological sex, instead of environmental exposures, influenced interactions with genes. Previous work had shown evidence of these gene-by-sex interactions, and we found additional examples of the effects of biological sex on all three types of gene-environment interactions. For example, we found that neuroticism had genetic effects that varied across sex. Finally, we also found that multiple types of gene-environment interactions can affect the same trait. For example, the effects of genetics on systolic blood pressure varied by sex, indicating that some genetic variants have different effects in men and women. How do we make sense of these distinct types of gene-environment interactions? We argue that they can help researchers better understand the underlying biological mechanisms that lead from genetic and environmental risks to disease, and how genetic variation leads to differences in disease risk between people. Genes related to the same function work together in a unit called a pathway. For example, we can say that genes involved in making heme – the component of red blood cells that carries oxygen – are collectively part of the heme synthesis pathway. The resulting amounts of heme circulating in the body influence other biological processes, including ones that could lead to the development of anemia and cancer. Our model suggests that environmental exposures modify different parts of these pathways, which may explain why we saw different types of gene-environment interactions. In the future, these findings could lead to treatments that are more personalized based on a person's genome. For example, clinicians might one day be able to tell whether someone is more likely to decrease their risk of heart disease by taking weight loss drugs or by exercising. Our results show how studying gene-environment interactions can tell researchers not only about which genetic and environmental factors increase your risk of disease, but also what goes wrong in the body where. This article is republished from The Conversation, a nonprofit, independent news organization bringing you facts and trustworthy analysis to help you make sense of our complex world. It was written by: Arun Durvasula, University of Southern California Read more: Your environment affects how well your medications work − identifying exactly how could make medicine better People don't mate randomly – but the flawed assumption that they do is an essential part of many studies linking genes to diseases and traits Researchers uncovered hundreds of genes linked to OCD, providing clues about how it changes the brain − new research Arun Durvasula has received funding from the National Institutes of Health and the National Institute of Science.
