The skin is not only our largest organ, but also the scene of numerous diseases. Using Raster-Scan Optoacoustic Mesoscopy (RSOM) that we have developed, we can look inside and under the skin to better understand and combat diseases such as skin cancer or psoriasis. Throughout the history of medicine, physicians have relied on surface features of the skin to gain insights into various diseases. Alterations in skin color or appearance often signify underlying conditions, whether localized to the skin or indicative of systemic issues. However, the human eye's capabilities are limited to superficial observation, lacking the ability to penetrate beneath the skin's surface and accurately assess what lies beneath. Similarly, conventional optical tools such as cameras and microscopes are confined to shallow depths of penetration. RSOM, however, revolutionizes this paradigm by facilitating highly detailed visualization deep within the layers of the skin. This innovative technology provides accurate depictions of various pathophysiological parameters, including intricate details of microvascular structure and function, as well as measurements of oxygenation and lipid content. These insights, obtained through RSOM, surpass the limitations of visual skin inspection, offering a more precise understanding of disease development and progression. In the WINTHER project (https://winther.munichimaging.eu/), we also use the skin as a window into diseases such as diabetes. We applied RSOM integrated with artificial intelligence (AI) to investigate diabetes-related skin changes. We captured high-resolution images of skin microstructures in both diabetic and non-diabetic individuals. AI algorithms were then employed to analyze these images, detecting subtle alterations indicative of diabetes, such as changes in blood vessel density and skin thickness. In this way, the stage and progression of diabetes can be monitored from taking quick, non-invasive images of the skin. In the OPTOMICS project (https://optomics.munichimaging.eu/), three worlds of science come together to revolutionize our understanding of diabetes: we combine optoacoustic imaging with the help of RSOM of diabetes patients with their multi-omics data (genome, proteome) and artificial intelligence. In this way, we create a digital twin model for type 2 diabetes.