diff --git a/src/spatialdata/_core/query/relational_query.py b/src/spatialdata/_core/query/relational_query.py
index 090cbca4..c9498a9c 100644
--- a/src/spatialdata/_core/query/relational_query.py
+++ b/src/spatialdata/_core/query/relational_query.py
@@ -97,8 +97,7 @@ def get_element_instances(
 
     Returns
     -------
-    pd.Series
-        The instances (index values) of the SpatialElement.
+    pd.Series with the instances (index values) of the SpatialElement.
     """
     raise ValueError(f"The object type {type(element)} is not supported.")
 
@@ -184,6 +183,8 @@ def _filter_table_by_elements(
                 instances = np.sort(instances)
             elif get_model(element) == ShapesModel:
                 instances = element.index.to_numpy()
+            elif get_model(element) == PointsModel:
+                instances = element.compute().index.to_numpy()
             else:
                 continue
             indices = ((table.obs[region_key] == name) & (table.obs[instance_key].isin(instances))).to_numpy()
@@ -785,7 +786,7 @@ def _locate_value(
         origins = _get_table_origins(element=el, value_key=value_key, origins=origins)
 
     # adding from the obs columns or var
-    if model in [ShapesModel, PointsModel, Labels2DModel, Labels3DModel] and sdata is not None:
+    if model in [PointsModel, ShapesModel, Labels2DModel, Labels3DModel] and sdata is not None:
         table = sdata.tables.get(table_name) if table_name is not None else None
         if table is not None:
             # check if the table is annotating the element
diff --git a/tests/core/query/test_relational_query.py b/tests/core/query/test_relational_query.py
index 80cd6d39..60b7bd36 100644
--- a/tests/core/query/test_relational_query.py
+++ b/tests/core/query/test_relational_query.py
@@ -520,7 +520,7 @@ def _check_location(locations: list[_ValueOrigin], origin: str, is_categorical:
     )
 
 
-def test_get_values_df(sdata_query_aggregation):
+def test_get_values_df_shapes(sdata_query_aggregation):
     # test with a single value, in the dataframe; using sdata + element_name
     v = get_values(
         value_key="numerical_in_gdf", sdata=sdata_query_aggregation, element_name="values_circles", table_name="table"
@@ -621,6 +621,28 @@ def test_get_values_df(sdata_query_aggregation):
         )
 
 
+def test_get_values_df_points(points):
+    # testing get_values() for points, we keep the test more minimalistic than the one for shapes
+    p = points["points_0"]
+    p = p.drop("instance_id", axis=1)
+    p.index.compute()
+    n = len(p)
+    obs = pd.DataFrame(index=p.index, data={"region": ["points_0"] * n, "instance_id": range(n)})
+    obs["region"] = obs["region"].astype("category")
+    table = TableModel.parse(
+        AnnData(shape=(n, 0), obs=obs), region="points_0", region_key="region", instance_key="instance_id"
+    )
+    points["points_0"] = p
+    points["table"] = table
+
+    assert get_values(value_key="region", element_name="points_0", sdata=points, table_name="table").shape == (300, 1)
+    get_values(value_key="instance_id", element_name="points_0", sdata=points, table_name="table")
+    get_values(value_key=["x", "y"], element_name="points_0", sdata=points, table_name="table")
+    get_values(value_key="genes", element_name="points_0", sdata=points, table_name="table")
+
+    pass
+
+
 def test_get_values_obsm(adata_labels: AnnData):
     get_values(value_key="tensor", element=adata_labels)